{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "os.chdir(\"../..\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********************\n",
      "\n",
      "   Going to generate c302_C2_AVB_VB and run for 4000 on jNeuroML_NEURON\n",
      "\n",
      "********************\n",
      "Set default parameters for C\n",
      "Set default parameters for C2\n",
      "Opened file: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/../../../herm_full_edgelist.csv\n",
      "Opened file: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/../../../herm_full_edgelist.csv\n",
      "c302      >>>  Positioning muscle: MDR01 at (80,-270,80)\n",
      "c302      >>>  Positioning muscle: MDR02 at (80,-240,80)\n",
      "c302      >>>  Positioning muscle: MDR03 at (80,-210,80)\n",
      "c302      >>>  Positioning muscle: MDR04 at (80,-180,80)\n",
      "c302      >>>  Positioning muscle: MDR05 at (80,-150,80)\n",
      "c302      >>>  Positioning muscle: MDR06 at (80,-120,80)\n",
      "c302      >>>  Positioning muscle: MDR07 at (80,-90,80)\n",
      "c302      >>>  Positioning muscle: MDR08 at (80,-60,80)\n",
      "c302      >>>  Positioning muscle: MDR09 at (80,-30,80)\n",
      "c302      >>>  Positioning muscle: MDR10 at (80,0,80)\n",
      "c302      >>>  Positioning muscle: MDR11 at (80,30,80)\n",
      "c302      >>>  Positioning muscle: MDR12 at (80,60,80)\n",
      "c302      >>>  Positioning muscle: MDR13 at (80,90,80)\n",
      "c302      >>>  Positioning muscle: MDR14 at (80,120,80)\n",
      "c302      >>>  Positioning muscle: MDR15 at (80,150,80)\n",
      "c302      >>>  Positioning muscle: MDR16 at (80,180,80)\n",
      "c302      >>>  Positioning muscle: MDR17 at (80,210,80)\n",
      "c302      >>>  Positioning muscle: MDR18 at (80,240,80)\n",
      "c302      >>>  Positioning muscle: MDR19 at (80,270,80)\n",
      "c302      >>>  Positioning muscle: MDR20 at (80,300,80)\n",
      "c302      >>>  Positioning muscle: MDR21 at (80,330,80)\n",
      "c302      >>>  Positioning muscle: MDR22 at (80,360,80)\n",
      "c302      >>>  Positioning muscle: MDR23 at (80,390,80)\n",
      "c302      >>>  Positioning muscle: MDR24 at (80,420,80)\n",
      "c302      >>>  Positioning muscle: MVR01 at (-80,-270,80)\n",
      "c302      >>>  Positioning muscle: MVR02 at (-80,-240,80)\n",
      "c302      >>>  Positioning muscle: MVR03 at (-80,-210,80)\n",
      "c302      >>>  Positioning muscle: MVR04 at (-80,-180,80)\n",
      "c302      >>>  Positioning muscle: MVR05 at (-80,-150,80)\n",
      "c302      >>>  Positioning muscle: MVR06 at (-80,-120,80)\n",
      "c302      >>>  Positioning muscle: MVR07 at (-80,-90,80)\n",
      "c302      >>>  Positioning muscle: MVR08 at (-80,-60,80)\n",
      "c302      >>>  Positioning muscle: MVR09 at (-80,-30,80)\n",
      "c302      >>>  Positioning muscle: MVR10 at (-80,0,80)\n",
      "c302      >>>  Positioning muscle: MVR11 at (-80,30,80)\n",
      "c302      >>>  Positioning muscle: MVR12 at (-80,60,80)\n",
      "c302      >>>  Positioning muscle: MVR13 at (-80,90,80)\n",
      "c302      >>>  Positioning muscle: MVR14 at (-80,120,80)\n",
      "c302      >>>  Positioning muscle: MVR15 at (-80,150,80)\n",
      "c302      >>>  Positioning muscle: MVR16 at (-80,180,80)\n",
      "c302      >>>  Positioning muscle: MVR17 at (-80,210,80)\n",
      "c302      >>>  Positioning muscle: MVR18 at (-80,240,80)\n",
      "c302      >>>  Positioning muscle: MVR19 at (-80,270,80)\n",
      "c302      >>>  Positioning muscle: MVR20 at (-80,300,80)\n",
      "c302      >>>  Positioning muscle: MVR21 at (-80,330,80)\n",
      "c302      >>>  Positioning muscle: MVR22 at (-80,360,80)\n",
      "c302      >>>  Positioning muscle: MVR23 at (-80,390,80)\n",
      "c302      >>>  Positioning muscle: MVL01 at (-80,-270,-80)\n",
      "c302      >>>  Positioning muscle: MVL02 at (-80,-240,-80)\n",
      "c302      >>>  Positioning muscle: MVL03 at (-80,-210,-80)\n",
      "c302      >>>  Positioning muscle: MVL04 at (-80,-180,-80)\n",
      "c302      >>>  Positioning muscle: MVL05 at (-80,-150,-80)\n",
      "c302      >>>  Positioning muscle: MVL06 at (-80,-120,-80)\n",
      "c302      >>>  Positioning muscle: MVL07 at (-80,-90,-80)\n",
      "c302      >>>  Positioning muscle: MVL08 at (-80,-60,-80)\n",
      "c302      >>>  Positioning muscle: MVL09 at (-80,-30,-80)\n",
      "c302      >>>  Positioning muscle: MVL10 at (-80,0,-80)\n",
      "c302      >>>  Positioning muscle: MVL11 at (-80,30,-80)\n",
      "c302      >>>  Positioning muscle: MVL12 at (-80,60,-80)\n",
      "c302      >>>  Positioning muscle: MVL13 at (-80,90,-80)\n",
      "c302      >>>  Positioning muscle: MVL14 at (-80,120,-80)\n",
      "c302      >>>  Positioning muscle: MVL15 at (-80,150,-80)\n",
      "c302      >>>  Positioning muscle: MVL16 at (-80,180,-80)\n",
      "c302      >>>  Positioning muscle: MVL17 at (-80,210,-80)\n",
      "c302      >>>  Positioning muscle: MVL18 at (-80,240,-80)\n",
      "c302      >>>  Positioning muscle: MVL19 at (-80,270,-80)\n",
      "c302      >>>  Positioning muscle: MVL20 at (-80,300,-80)\n",
      "c302      >>>  Positioning muscle: MVL21 at (-80,330,-80)\n",
      "c302      >>>  Positioning muscle: MVL22 at (-80,360,-80)\n",
      "c302      >>>  Positioning muscle: MVL23 at (-80,390,-80)\n",
      "c302      >>>  Positioning muscle: MVL24 at (-80,420,-80)\n",
      "c302      >>>  Positioning muscle: MDL01 at (80,-270,-80)\n",
      "c302      >>>  Positioning muscle: MDL02 at (80,-240,-80)\n",
      "c302      >>>  Positioning muscle: MDL03 at (80,-210,-80)\n",
      "c302      >>>  Positioning muscle: MDL04 at (80,-180,-80)\n",
      "c302      >>>  Positioning muscle: MDL05 at (80,-150,-80)\n",
      "c302      >>>  Positioning muscle: MDL06 at (80,-120,-80)\n",
      "c302      >>>  Positioning muscle: MDL07 at (80,-90,-80)\n",
      "c302      >>>  Positioning muscle: MDL08 at (80,-60,-80)\n",
      "c302      >>>  Positioning muscle: MDL09 at (80,-30,-80)\n",
      "c302      >>>  Positioning muscle: MDL10 at (80,0,-80)\n",
      "c302      >>>  Positioning muscle: MDL11 at (80,30,-80)\n",
      "c302      >>>  Positioning muscle: MDL12 at (80,60,-80)\n",
      "c302      >>>  Positioning muscle: MDL13 at (80,90,-80)\n",
      "c302      >>>  Positioning muscle: MDL14 at (80,120,-80)\n",
      "c302      >>>  Positioning muscle: MDL15 at (80,150,-80)\n",
      "c302      >>>  Positioning muscle: MDL16 at (80,180,-80)\n",
      "c302      >>>  Positioning muscle: MDL17 at (80,210,-80)\n",
      "c302      >>>  Positioning muscle: MDL18 at (80,240,-80)\n",
      "c302      >>>  Positioning muscle: MDL19 at (80,270,-80)\n",
      "c302      >>>  Positioning muscle: MDL20 at (80,300,-80)\n",
      "c302      >>>  Positioning muscle: MDL21 at (80,330,-80)\n",
      "c302      >>>  Positioning muscle: MDL22 at (80,360,-80)\n",
      "c302      >>>  Positioning muscle: MDL23 at (80,390,-80)\n",
      "c302      >>>  Positioning muscle: MDL24 at (80,420,-80)\n",
      "AVBL-AVBR 6 exc Acetylcholine\n",
      "AVBL-VB2 3 exc Acetylcholine\n",
      "AVBR-AVBL 2 exc Acetylcholine\n",
      "VB4-VB5 1 exc Acetylcholine\n",
      "AVBL-AVBR_GJ 17 exc Generic_GJ\n",
      "AVBL-VB1_GJ 1 exc Generic_GJ\n",
      "AVBL-VB2_GJ 14 exc Generic_GJ\n",
      "AVBL-VB4_GJ 3 exc Generic_GJ\n",
      "AVBL-VB5_GJ 3 exc Generic_GJ\n",
      "AVBL-VB6_GJ 3 exc Generic_GJ\n",
      "AVBL-VB7_GJ 4 exc Generic_GJ\n",
      "AVBL-VB8_GJ 4 exc Generic_GJ\n",
      "AVBL-VB9_GJ 3 exc Generic_GJ\n",
      "AVBL-VB10_GJ 4 exc Generic_GJ\n",
      "AVBL-VB11_GJ 5 exc Generic_GJ\n",
      "AVBR-AVBL_GJ 17 exc Generic_GJ\n",
      "AVBR-VB2_GJ 6 exc Generic_GJ\n",
      "AVBR-VB3_GJ 7 exc Generic_GJ\n",
      "AVBR-VB4_GJ 5 exc Generic_GJ\n",
      "AVBR-VB5_GJ 3 exc Generic_GJ\n",
      "AVBR-VB6_GJ 4 exc Generic_GJ\n",
      "AVBR-VB7_GJ 3 exc Generic_GJ\n",
      "AVBR-VB8_GJ 3 exc Generic_GJ\n",
      "AVBR-VB9_GJ 4 exc Generic_GJ\n",
      "AVBR-VB10_GJ 3 exc Generic_GJ\n",
      "AVBR-VB11_GJ 6 exc Generic_GJ\n",
      "VB1-AVBL_GJ 1 exc Generic_GJ\n",
      "VB1-VB2_GJ 2 exc Generic_GJ\n",
      "VB2-AVBL_GJ 14 exc Generic_GJ\n",
      "VB2-AVBR_GJ 6 exc Generic_GJ\n",
      "VB2-VB1_GJ 2 exc Generic_GJ\n",
      "VB2-VB3_GJ 10 exc Generic_GJ\n",
      "VB2-VB4_GJ 1 exc Generic_GJ\n",
      "VB3-AVBR_GJ 7 exc Generic_GJ\n",
      "VB3-VB2_GJ 10 exc Generic_GJ\n",
      "VB3-VB4_GJ 1 exc Generic_GJ\n",
      "VB4-AVBL_GJ 3 exc Generic_GJ\n",
      "VB4-AVBR_GJ 5 exc Generic_GJ\n",
      "VB4-VB2_GJ 1 exc Generic_GJ\n",
      "VB4-VB3_GJ 1 exc Generic_GJ\n",
      "VB4-VB5_GJ 1 exc Generic_GJ\n",
      "VB5-AVBL_GJ 3 exc Generic_GJ\n",
      "VB5-AVBR_GJ 3 exc Generic_GJ\n",
      "VB5-VB4_GJ 1 exc Generic_GJ\n",
      "VB5-VB6_GJ 5 exc Generic_GJ\n",
      "VB6-AVBL_GJ 3 exc Generic_GJ\n",
      "VB6-AVBR_GJ 4 exc Generic_GJ\n",
      "VB6-VB5_GJ 5 exc Generic_GJ\n",
      "VB6-VB7_GJ 5 exc Generic_GJ\n",
      "VB7-AVBL_GJ 4 exc Generic_GJ\n",
      "VB7-AVBR_GJ 3 exc Generic_GJ\n",
      "VB7-VB6_GJ 5 exc Generic_GJ\n",
      "VB7-VB8_GJ 5 exc Generic_GJ\n",
      "VB8-AVBL_GJ 3 exc Generic_GJ\n",
      "VB8-AVBR_GJ 4 exc Generic_GJ\n",
      "VB8-VB7_GJ 5 exc Generic_GJ\n",
      "VB8-VB9_GJ 5 exc Generic_GJ\n",
      "VB9-AVBL_GJ 4 exc Generic_GJ\n",
      "VB9-AVBR_GJ 3 exc Generic_GJ\n",
      "VB9-VB8_GJ 5 exc Generic_GJ\n",
      "VB9-VB10_GJ 5 exc Generic_GJ\n",
      "VB10-AVBL_GJ 3 exc Generic_GJ\n",
      "VB10-AVBR_GJ 4 exc Generic_GJ\n",
      "VB10-VB9_GJ 5 exc Generic_GJ\n",
      "VB10-VB11_GJ 4 exc Generic_GJ\n",
      "VB11-AVBL_GJ 5 exc Generic_GJ\n",
      "VB11-AVBR_GJ 6 exc Generic_GJ\n",
      "VB11-VB10_GJ 4 exc Generic_GJ\n",
      "AVBR-MVL16 1 exc Acetylcholine\n",
      "VB1-MVL07 2 exc Acetylcholine\n",
      "VB1-MVR07 5 exc Acetylcholine\n",
      "VB1-MVR09 1 exc Acetylcholine\n",
      "VB2-MVL08 2 exc Acetylcholine\n",
      "VB2-MVL09 14 exc Acetylcholine\n",
      "VB2-MVL10 4 exc Acetylcholine\n",
      "VB2-MVL11 1 exc Acetylcholine\n",
      "VB2-MVR08 6 exc Acetylcholine\n",
      "VB2-MVR10 10 exc Acetylcholine\n",
      "VB2-MVR11 6 exc Acetylcholine\n",
      "VB3-MVL10 1 exc Acetylcholine\n",
      "VB3-MVL11 8 exc Acetylcholine\n",
      "VB3-MVL12 8 exc Acetylcholine\n",
      "VB3-MVL13 3 exc Acetylcholine\n",
      "VB3-MVR10 4 exc Acetylcholine\n",
      "VB3-MVR11 6 exc Acetylcholine\n",
      "VB3-MVR12 8 exc Acetylcholine\n",
      "VB3-MVR13 4 exc Acetylcholine\n",
      "VB4-MVL12 3 exc Acetylcholine\n",
      "VB4-MVL13 5 exc Acetylcholine\n",
      "VB4-MVR12 3 exc Acetylcholine\n",
      "VB4-MVR13 3 exc Acetylcholine\n",
      "VB4-MVR14 4 exc Acetylcholine\n",
      "VB5-MVL12 3 exc Acetylcholine\n",
      "VB5-MVL13 1 exc Acetylcholine\n",
      "VB5-MVL14 8 exc Acetylcholine\n",
      "VB5-MVL15 7 exc Acetylcholine\n",
      "VB5-MVR13 7 exc Acetylcholine\n",
      "VB5-MVR14 6 exc Acetylcholine\n",
      "VB5-MVR15 1 exc Acetylcholine\n",
      "VB6-MVL15 4 exc Acetylcholine\n",
      "VB6-MVL16 3 exc Acetylcholine\n",
      "VB6-MVR14 6 exc Acetylcholine\n",
      "VB6-MVR15 12 exc Acetylcholine\n",
      "VB6-MVR16 4 exc Acetylcholine\n",
      "VB7-MVL16 4 exc Acetylcholine\n",
      "VB7-MVL17 4 exc Acetylcholine\n",
      "VB7-MVL18 4 exc Acetylcholine\n",
      "VB7-MVR16 4 exc Acetylcholine\n",
      "VB7-MVR17 4 exc Acetylcholine\n",
      "VB7-MVR18 4 exc Acetylcholine\n",
      "VB8-MVL18 4 exc Acetylcholine\n",
      "VB8-MVL19 4 exc Acetylcholine\n",
      "VB8-MVL20 4 exc Acetylcholine\n",
      "VB8-MVR18 4 exc Acetylcholine\n",
      "VB8-MVR19 4 exc Acetylcholine\n",
      "VB8-MVR20 4 exc Acetylcholine\n",
      "VB9-MVL19 4 exc Acetylcholine\n",
      "VB9-MVL20 4 exc Acetylcholine\n",
      "VB9-MVL21 4 exc Acetylcholine\n",
      "VB9-MVR19 4 exc Acetylcholine\n",
      "VB9-MVR20 4 exc Acetylcholine\n",
      "VB9-MVR21 4 exc Acetylcholine\n",
      "VB10-MVL20 4 exc Acetylcholine\n",
      "VB10-MVL21 4 exc Acetylcholine\n",
      "VB10-MVL22 4 exc Acetylcholine\n",
      "VB10-MVR20 4 exc Acetylcholine\n",
      "VB10-MVR21 4 exc Acetylcholine\n",
      "VB10-MVR22 4 exc Acetylcholine\n",
      "VB11-MVL21 4 exc Acetylcholine\n",
      "VB11-MVL22 4 exc Acetylcholine\n",
      "VB11-MVL23 4 exc Acetylcholine\n",
      "VB11-MVR21 4 exc Acetylcholine\n",
      "VB11-MVR22 4 exc Acetylcholine\n",
      "VB11-MVR23 4 exc Acetylcholine\n",
      "MDL01-MDL02_GJ 15 exc Generic_GJ\n",
      "MDL01-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL02-MDL01_GJ 15 exc Generic_GJ\n",
      "MDL02-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL01_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL02_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL04_GJ 15 exc Generic_GJ\n",
      "MDL04-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL04-MDL05_GJ 15 exc Generic_GJ\n",
      "MDL05-MDL04_GJ 15 exc Generic_GJ\n",
      "MDL05-MDL06_GJ 15 exc Generic_GJ\n",
      "MDL06-MDL05_GJ 15 exc Generic_GJ\n",
      "MDL06-MDL07_GJ 15 exc Generic_GJ\n",
      "MDL07-MDL06_GJ 15 exc Generic_GJ\n",
      "MDL07-MDL08_GJ 15 exc Generic_GJ\n",
      "MDL08-MDL07_GJ 15 exc Generic_GJ\n",
      "MDL08-MDL09_GJ 15 exc Generic_GJ\n",
      "MDL09-MDL08_GJ 15 exc Generic_GJ\n",
      "MDL09-MDL10_GJ 15 exc Generic_GJ\n",
      "MDL10-MDL09_GJ 15 exc Generic_GJ\n",
      "MDL10-MDL11_GJ 15 exc Generic_GJ\n",
      "MDL11-MDL10_GJ 15 exc Generic_GJ\n",
      "MDL11-MDL12_GJ 15 exc Generic_GJ\n",
      "MDL12-MDL11_GJ 15 exc Generic_GJ\n",
      "MDL12-MDL13_GJ 15 exc Generic_GJ\n",
      "MDL13-MDL12_GJ 15 exc Generic_GJ\n",
      "MDL13-MDL14_GJ 15 exc Generic_GJ\n",
      "MDL14-MDL13_GJ 15 exc Generic_GJ\n",
      "MDL14-MDL15_GJ 15 exc Generic_GJ\n",
      "MDL15-MDL14_GJ 15 exc Generic_GJ\n",
      "MDL15-MDL16_GJ 15 exc Generic_GJ\n",
      "MDL16-MDL15_GJ 15 exc Generic_GJ\n",
      "MDL16-MDL17_GJ 15 exc Generic_GJ\n",
      "MDL17-MDL16_GJ 15 exc Generic_GJ\n",
      "MDL17-MDL18_GJ 15 exc Generic_GJ\n",
      "MDL18-MDL17_GJ 15 exc Generic_GJ\n",
      "MDL18-MDL19_GJ 15 exc Generic_GJ\n",
      "MDL19-MDL18_GJ 15 exc Generic_GJ\n",
      "MDL19-MDL20_GJ 15 exc Generic_GJ\n",
      "MDL20-MDL19_GJ 15 exc Generic_GJ\n",
      "MDL20-MDL21_GJ 15 exc Generic_GJ\n",
      "MDL21-MDL20_GJ 15 exc Generic_GJ\n",
      "MDL21-MDL22_GJ 15 exc Generic_GJ\n",
      "MDL22-MDL21_GJ 15 exc Generic_GJ\n",
      "MDL22-MDL23_GJ 15 exc Generic_GJ\n",
      "MDL23-MDL22_GJ 15 exc Generic_GJ\n",
      "MDL23-MDL24_GJ 15 exc Generic_GJ\n",
      "MDL24-MDL23_GJ 15 exc Generic_GJ\n",
      "MDR01-MDR02_GJ 15 exc Generic_GJ\n",
      "MDR01-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR02-MDR01_GJ 15 exc Generic_GJ\n",
      "MDR02-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR01_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR02_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR04_GJ 15 exc Generic_GJ\n",
      "MDR04-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR04-MDR05_GJ 15 exc Generic_GJ\n",
      "MDR05-MDR04_GJ 15 exc Generic_GJ\n",
      "MDR05-MDR06_GJ 15 exc Generic_GJ\n",
      "MDR06-MDR05_GJ 15 exc Generic_GJ\n",
      "MDR06-MDR07_GJ 15 exc Generic_GJ\n",
      "MDR07-MDR06_GJ 15 exc Generic_GJ\n",
      "MDR07-MDR08_GJ 15 exc Generic_GJ\n",
      "MDR08-MDR07_GJ 15 exc Generic_GJ\n",
      "MDR08-MDR09_GJ 15 exc Generic_GJ\n",
      "MDR09-MDR08_GJ 15 exc Generic_GJ\n",
      "MDR09-MDR10_GJ 15 exc Generic_GJ\n",
      "MDR10-MDR09_GJ 15 exc Generic_GJ\n",
      "MDR10-MDR11_GJ 15 exc Generic_GJ\n",
      "MDR11-MDR10_GJ 15 exc Generic_GJ\n",
      "MDR11-MDR12_GJ 15 exc Generic_GJ\n",
      "MDR12-MDR11_GJ 15 exc Generic_GJ\n",
      "MDR12-MDR13_GJ 15 exc Generic_GJ\n",
      "MDR13-MDR12_GJ 15 exc Generic_GJ\n",
      "MDR13-MDR14_GJ 15 exc Generic_GJ\n",
      "MDR14-MDR13_GJ 15 exc Generic_GJ\n",
      "MDR14-MDR15_GJ 15 exc Generic_GJ\n",
      "MDR15-MDR14_GJ 15 exc Generic_GJ\n",
      "MDR15-MDR16_GJ 15 exc Generic_GJ\n",
      "MDR16-MDR15_GJ 15 exc Generic_GJ\n",
      "MDR16-MDR17_GJ 15 exc Generic_GJ\n",
      "MDR17-MDR16_GJ 15 exc Generic_GJ\n",
      "MDR17-MDR18_GJ 15 exc Generic_GJ\n",
      "MDR18-MDR17_GJ 15 exc Generic_GJ\n",
      "MDR18-MDR19_GJ 15 exc Generic_GJ\n",
      "MDR19-MDR18_GJ 15 exc Generic_GJ\n",
      "MDR19-MDR20_GJ 15 exc Generic_GJ\n",
      "MDR20-MDR19_GJ 15 exc Generic_GJ\n",
      "MDR20-MDR21_GJ 15 exc Generic_GJ\n",
      "MDR21-MDR20_GJ 15 exc Generic_GJ\n",
      "MDR21-MDR22_GJ 15 exc Generic_GJ\n",
      "MDR22-MDR21_GJ 15 exc Generic_GJ\n",
      "MDR22-MDR23_GJ 15 exc Generic_GJ\n",
      "MDR23-MDR22_GJ 15 exc Generic_GJ\n",
      "MDR23-MDR24_GJ 15 exc Generic_GJ\n",
      "MDR24-MDR23_GJ 15 exc Generic_GJ\n",
      "MVL01-MVL02_GJ 15 exc Generic_GJ\n",
      "MVL01-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL02-MVL01_GJ 15 exc Generic_GJ\n",
      "MVL02-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL01_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL02_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL04_GJ 15 exc Generic_GJ\n",
      "MVL04-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL04-MVL05_GJ 15 exc Generic_GJ\n",
      "MVL05-MVL04_GJ 15 exc Generic_GJ\n",
      "MVL05-MVL06_GJ 15 exc Generic_GJ\n",
      "MVL06-MVL05_GJ 15 exc Generic_GJ\n",
      "MVL06-MVL07_GJ 15 exc Generic_GJ\n",
      "MVL07-MVL06_GJ 15 exc Generic_GJ\n",
      "MVL07-MVL08_GJ 15 exc Generic_GJ\n",
      "MVL08-MVL07_GJ 15 exc Generic_GJ\n",
      "MVL08-MVL09_GJ 15 exc Generic_GJ\n",
      "MVL09-MVL08_GJ 15 exc Generic_GJ\n",
      "MVL09-MVL10_GJ 15 exc Generic_GJ\n",
      "MVL09-MVR08_GJ 2 exc Generic_GJ\n",
      "MVL10-MVL09_GJ 15 exc Generic_GJ\n",
      "MVL10-MVL11_GJ 15 exc Generic_GJ\n",
      "MVL11-MVL10_GJ 15 exc Generic_GJ\n",
      "MVL11-MVL12_GJ 15 exc Generic_GJ\n",
      "MVL12-MVL11_GJ 15 exc Generic_GJ\n",
      "MVL12-MVL13_GJ 15 exc Generic_GJ\n",
      "MVL13-MVL12_GJ 15 exc Generic_GJ\n",
      "MVL13-MVL14_GJ 15 exc Generic_GJ\n",
      "MVL14-MVL13_GJ 15 exc Generic_GJ\n",
      "MVL14-MVL15_GJ 15 exc Generic_GJ\n",
      "MVL15-MVL14_GJ 15 exc Generic_GJ\n",
      "MVL15-MVL16_GJ 15 exc Generic_GJ\n",
      "MVL16-MVL15_GJ 15 exc Generic_GJ\n",
      "MVL16-MVL17_GJ 15 exc Generic_GJ\n",
      "MVL17-MVL16_GJ 15 exc Generic_GJ\n",
      "MVL17-MVL18_GJ 15 exc Generic_GJ\n",
      "MVL18-MVL17_GJ 15 exc Generic_GJ\n",
      "MVL18-MVL19_GJ 15 exc Generic_GJ\n",
      "MVL19-MVL18_GJ 15 exc Generic_GJ\n",
      "MVL19-MVL20_GJ 15 exc Generic_GJ\n",
      "MVL20-MVL19_GJ 15 exc Generic_GJ\n",
      "MVL20-MVL21_GJ 15 exc Generic_GJ\n",
      "MVL21-MVL20_GJ 15 exc Generic_GJ\n",
      "MVL21-MVL22_GJ 15 exc Generic_GJ\n",
      "MVL22-MVL21_GJ 15 exc Generic_GJ\n",
      "MVL22-MVL23_GJ 15 exc Generic_GJ\n",
      "MVL23-MVL22_GJ 15 exc Generic_GJ\n",
      "MVR01-MVR02_GJ 15 exc Generic_GJ\n",
      "MVR01-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR02-MVR01_GJ 15 exc Generic_GJ\n",
      "MVR02-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR01_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR02_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR04_GJ 15 exc Generic_GJ\n",
      "MVR04-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR04-MVR05_GJ 15 exc Generic_GJ\n",
      "MVR05-MVR04_GJ 15 exc Generic_GJ\n",
      "MVR05-MVR06_GJ 15 exc Generic_GJ\n",
      "MVR06-MVR05_GJ 15 exc Generic_GJ\n",
      "MVR06-MVR07_GJ 15 exc Generic_GJ\n",
      "MVR07-MVR06_GJ 15 exc Generic_GJ\n",
      "MVR07-MVR08_GJ 15 exc Generic_GJ\n",
      "MVR08-MVL09_GJ 2 exc Generic_GJ\n",
      "MVR08-MVR07_GJ 15 exc Generic_GJ\n",
      "MVR08-MVR09_GJ 15 exc Generic_GJ\n",
      "MVR09-MVR08_GJ 15 exc Generic_GJ\n",
      "MVR09-MVR10_GJ 15 exc Generic_GJ\n",
      "MVR10-MVR09_GJ 15 exc Generic_GJ\n",
      "MVR10-MVR11_GJ 15 exc Generic_GJ\n",
      "MVR11-MVR10_GJ 15 exc Generic_GJ\n",
      "MVR11-MVR12_GJ 15 exc Generic_GJ\n",
      "MVR12-MVR11_GJ 15 exc Generic_GJ\n",
      "MVR12-MVR13_GJ 15 exc Generic_GJ\n",
      "MVR13-MVR12_GJ 15 exc Generic_GJ\n",
      "MVR13-MVR14_GJ 15 exc Generic_GJ\n",
      "MVR14-MVR13_GJ 15 exc Generic_GJ\n",
      "MVR14-MVR15_GJ 15 exc Generic_GJ\n",
      "MVR15-MVR14_GJ 15 exc Generic_GJ\n",
      "MVR15-MVR16_GJ 15 exc Generic_GJ\n",
      "MVR16-MVR15_GJ 15 exc Generic_GJ\n",
      "MVR16-MVR17_GJ 15 exc Generic_GJ\n",
      "MVR17-MVR16_GJ 15 exc Generic_GJ\n",
      "MVR17-MVR18_GJ 15 exc Generic_GJ\n",
      "MVR18-MVR17_GJ 15 exc Generic_GJ\n",
      "MVR18-MVR19_GJ 15 exc Generic_GJ\n",
      "MVR19-MVR18_GJ 15 exc Generic_GJ\n",
      "MVR19-MVR20_GJ 15 exc Generic_GJ\n",
      "MVR20-MVR19_GJ 15 exc Generic_GJ\n",
      "MVR20-MVR21_GJ 15 exc Generic_GJ\n",
      "MVR21-MVR20_GJ 15 exc Generic_GJ\n",
      "MVR21-MVR22_GJ 15 exc Generic_GJ\n",
      "MVR22-MVR21_GJ 15 exc Generic_GJ\n",
      "MVR22-MVR23_GJ 15 exc Generic_GJ\n",
      "MVR23-MVR22_GJ 15 exc Generic_GJ\n",
      "c302      >>>  Writing generated network to: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/examples/c302_C2_AVB_VB.nml\n",
      "Validating examples/c302_C2_AVB_VB.nml against /usr/local/lib/python2.7/dist-packages/neuroml/nml/NeuroML_v2beta4.xsd\n",
      "It's valid!\n",
      "(Re)written network file to: examples/c302_C2_AVB_VB.nml\n",
      "c302      >>>  Finished simulation of LEMS_c302_C2_AVB_VB.xml and have reloaded results\n",
      "c302      >>>  Reloaded data: ['MVL16/0/GenericMuscleCell/caConc', 'MDR14/0/GenericMuscleCell/caConc', 'MDR20/0/GenericMuscleCell/caConc', 'MDR14/0/GenericMuscleCell/v', 'MVL19/0/GenericMuscleCell/caConc', 'MVL24/0/GenericMuscleCell/v', 'MVL22/0/GenericMuscleCell/v', 'MDL13/0/GenericMuscleCell/v', 'MVR02/0/GenericMuscleCell/v', 'MDR21/0/GenericMuscleCell/caConc', 'MDL08/0/GenericMuscleCell/v', 'VB2/0/GenericNeuronCell/caConc', 'MVR09/0/GenericMuscleCell/caConc', 'MDR10/0/GenericMuscleCell/v', 'MVL07/0/GenericMuscleCell/v', 'MVR05/0/GenericMuscleCell/v', 'MVL24/0/GenericMuscleCell/caConc', 'VB11/0/GenericNeuronCell/v', 'MDR18/0/GenericMuscleCell/v', 'MDR04/0/GenericMuscleCell/caConc', 'MVL10/0/GenericMuscleCell/v', 'MDR13/0/GenericMuscleCell/caConc', 'VB1/0/GenericNeuronCell/v', 'MDR11/0/GenericMuscleCell/v', 'MDL09/0/GenericMuscleCell/v', 'MVR04/0/GenericMuscleCell/v', 'MVL05/0/GenericMuscleCell/v', 'MVR19/0/GenericMuscleCell/caConc', 'MVR10/0/GenericMuscleCell/v', 'MDR17/0/GenericMuscleCell/v', 'VB1/0/GenericNeuronCell/caConc', 'MDL23/0/GenericMuscleCell/v', 'MDR03/0/GenericMuscleCell/caConc', 'MVL07/0/GenericMuscleCell/caConc', 'MDL06/0/GenericMuscleCell/v', 'MDR18/0/GenericMuscleCell/caConc', 'MDL11/0/GenericMuscleCell/v', 'MVL12/0/GenericMuscleCell/v', 'MVR01/0/GenericMuscleCell/v', 'VB7/0/GenericNeuronCell/v', 'MDR19/0/GenericMuscleCell/v', 'MDL16/0/GenericMuscleCell/caConc', 'MDL05/0/GenericMuscleCell/caConc', 'MDL24/0/GenericMuscleCell/v', 'MDL02/0/GenericMuscleCell/caConc', 'MVR21/0/GenericMuscleCell/v', 'MVL01/0/GenericMuscleCell/caConc', 'VB3/0/GenericNeuronCell/v', 'VB2/0/GenericNeuronCell/v', 'MVL06/0/GenericMuscleCell/v', 'MDR13/0/GenericMuscleCell/v', 'MDL19/0/GenericMuscleCell/caConc', 'MDL16/0/GenericMuscleCell/v', 'MDR11/0/GenericMuscleCell/caConc', 'MVL05/0/GenericMuscleCell/caConc', 'VB5/0/GenericNeuronCell/caConc', 'VB3/0/GenericNeuronCell/caConc', 'AVBL/0/GenericNeuronCell/v', 'MVL20/0/GenericMuscleCell/caConc', 'VB9/0/GenericNeuronCell/v', 'MDR16/0/GenericMuscleCell/caConc', 'MDR05/0/GenericMuscleCell/v', 'MDL04/0/GenericMuscleCell/caConc', 'MVR23/0/GenericMuscleCell/caConc', 'MDR09/0/GenericMuscleCell/v', 'MVL14/0/GenericMuscleCell/v', 'MDR15/0/GenericMuscleCell/v', 'MVR22/0/GenericMuscleCell/v', 'MVR14/0/GenericMuscleCell/v', 'MDL12/0/GenericMuscleCell/caConc', 'VB6/0/GenericNeuronCell/v', 'MDL20/0/GenericMuscleCell/v', 'MVR18/0/GenericMuscleCell/v', 'MDL17/0/GenericMuscleCell/v', 'MVL22/0/GenericMuscleCell/caConc', 'MVL03/0/GenericMuscleCell/caConc', 'MDR02/0/GenericMuscleCell/v', 'MVL04/0/GenericMuscleCell/v', 'MDL08/0/GenericMuscleCell/caConc', 'MVR19/0/GenericMuscleCell/v', 'MVR05/0/GenericMuscleCell/caConc', 'MDL06/0/GenericMuscleCell/caConc', 't', 'VB11/0/GenericNeuronCell/caConc', 'MDL03/0/GenericMuscleCell/caConc', 'MVL19/0/GenericMuscleCell/v', 'MDR05/0/GenericMuscleCell/caConc', 'MVR23/0/GenericMuscleCell/v', 'MVL16/0/GenericMuscleCell/v', 'MDL17/0/GenericMuscleCell/caConc', 'MVR16/0/GenericMuscleCell/caConc', 'MDR15/0/GenericMuscleCell/caConc', 'MVL02/0/GenericMuscleCell/v', 'VB4/0/GenericNeuronCell/v', 'MVR17/0/GenericMuscleCell/v', 'MDL18/0/GenericMuscleCell/v', 'MVR07/0/GenericMuscleCell/v', 'MDL14/0/GenericMuscleCell/caConc', 'VB9/0/GenericNeuronCell/caConc', 'MDL23/0/GenericMuscleCell/caConc', 'MVL18/0/GenericMuscleCell/v', 'MVL15/0/GenericMuscleCell/caConc', 'MVL23/0/GenericMuscleCell/caConc', 'MVR20/0/GenericMuscleCell/caConc', 'MVL09/0/GenericMuscleCell/v', 'MVR06/0/GenericMuscleCell/v', 'MDL01/0/GenericMuscleCell/caConc', 'MDR12/0/GenericMuscleCell/caConc', 'MVL08/0/GenericMuscleCell/caConc', 'VB5/0/GenericNeuronCell/v', 'MDR10/0/GenericMuscleCell/caConc', 'MDR04/0/GenericMuscleCell/v', 'MDR23/0/GenericMuscleCell/caConc', 'MVR16/0/GenericMuscleCell/v', 'MDL18/0/GenericMuscleCell/caConc', 'MDL10/0/GenericMuscleCell/caConc', 'MDL07/0/GenericMuscleCell/caConc', 'MVL06/0/GenericMuscleCell/caConc', 'MDR20/0/GenericMuscleCell/v', 'MDR23/0/GenericMuscleCell/v', 'MDL22/0/GenericMuscleCell/caConc', 'MVL10/0/GenericMuscleCell/caConc', 'MVR08/0/GenericMuscleCell/v', 'MVR20/0/GenericMuscleCell/v', 'MDL03/0/GenericMuscleCell/v', 'MVL09/0/GenericMuscleCell/caConc', 'MVL21/0/GenericMuscleCell/caConc', 'MVL20/0/GenericMuscleCell/v', 'VB8/0/GenericNeuronCell/caConc', 'VB4/0/GenericNeuronCell/caConc', 'MVL15/0/GenericMuscleCell/v', 'MVL13/0/GenericMuscleCell/caConc', 'MDL02/0/GenericMuscleCell/v', 'MDR06/0/GenericMuscleCell/v', 'MDR01/0/GenericMuscleCell/caConc', 'MDR07/0/GenericMuscleCell/caConc', 'MVR11/0/GenericMuscleCell/caConc', 'MVR18/0/GenericMuscleCell/caConc', 'MDL11/0/GenericMuscleCell/caConc', 'MDR07/0/GenericMuscleCell/v', 'MDL10/0/GenericMuscleCell/v', 'MVR09/0/GenericMuscleCell/v', 'MDL04/0/GenericMuscleCell/v', 'MVL02/0/GenericMuscleCell/caConc', 'MVL14/0/GenericMuscleCell/caConc', 'MDR17/0/GenericMuscleCell/caConc', 'MDL13/0/GenericMuscleCell/caConc', 'MDR06/0/GenericMuscleCell/caConc', 'MDR03/0/GenericMuscleCell/v', 'MDL22/0/GenericMuscleCell/v', 'MDR08/0/GenericMuscleCell/v', 'MDL01/0/GenericMuscleCell/v', 'MVL01/0/GenericMuscleCell/v', 'MDL12/0/GenericMuscleCell/v', 'MVR15/0/GenericMuscleCell/v', 'MVL04/0/GenericMuscleCell/caConc', 'AVBL/0/GenericNeuronCell/caConc', 'MVL18/0/GenericMuscleCell/caConc', 'MDL09/0/GenericMuscleCell/caConc', 'MDL20/0/GenericMuscleCell/caConc', 'MVL17/0/GenericMuscleCell/v', 'MVR11/0/GenericMuscleCell/v', 'MVL12/0/GenericMuscleCell/caConc', 'MDR12/0/GenericMuscleCell/v', 'AVBR/0/GenericNeuronCell/v', 'MVL23/0/GenericMuscleCell/v', 'MVR06/0/GenericMuscleCell/caConc', 'MVR02/0/GenericMuscleCell/caConc', 'MDL21/0/GenericMuscleCell/v', 'MVR07/0/GenericMuscleCell/caConc', 'MDR24/0/GenericMuscleCell/v', 'MDR09/0/GenericMuscleCell/caConc', 'MVL08/0/GenericMuscleCell/v', 'MVR01/0/GenericMuscleCell/caConc', 'MVR03/0/GenericMuscleCell/v', 'MVR17/0/GenericMuscleCell/caConc', 'MVR22/0/GenericMuscleCell/caConc', 'MVR13/0/GenericMuscleCell/v', 'MVR21/0/GenericMuscleCell/caConc', 'MVR04/0/GenericMuscleCell/caConc', 'MDL05/0/GenericMuscleCell/v', 'MDL24/0/GenericMuscleCell/caConc', 'AVBR/0/GenericNeuronCell/caConc', 'MDL15/0/GenericMuscleCell/caConc', 'MVR10/0/GenericMuscleCell/caConc', 'MDL14/0/GenericMuscleCell/v', 'MDR19/0/GenericMuscleCell/caConc', 'MVL03/0/GenericMuscleCell/v', 'MDL21/0/GenericMuscleCell/caConc', 'MVL17/0/GenericMuscleCell/caConc', 'MVL21/0/GenericMuscleCell/v', 'MDR01/0/GenericMuscleCell/v', 'MVR12/0/GenericMuscleCell/v', 'MVR13/0/GenericMuscleCell/caConc', 'MVL11/0/GenericMuscleCell/v', 'MDR02/0/GenericMuscleCell/caConc', 'MDR24/0/GenericMuscleCell/caConc', 'MVL11/0/GenericMuscleCell/caConc', 'MDL07/0/GenericMuscleCell/v', 'MVR08/0/GenericMuscleCell/caConc', 'MDR22/0/GenericMuscleCell/caConc', 'MVR14/0/GenericMuscleCell/caConc', 'MVR12/0/GenericMuscleCell/caConc', 'MVL13/0/GenericMuscleCell/v', 'MDL15/0/GenericMuscleCell/v', 'MVR03/0/GenericMuscleCell/caConc', 'MDR08/0/GenericMuscleCell/caConc', 'VB10/0/GenericNeuronCell/v', 'MDR22/0/GenericMuscleCell/v', 'MDL19/0/GenericMuscleCell/v', 'MDR16/0/GenericMuscleCell/v', 'MDR21/0/GenericMuscleCell/v', 'VB7/0/GenericNeuronCell/caConc', 'VB6/0/GenericNeuronCell/caConc', 'VB10/0/GenericNeuronCell/caConc', 'VB8/0/GenericNeuronCell/v', 'MVR15/0/GenericMuscleCell/caConc']\n",
      "c302      >>>  All cells: ['VB11', 'VB10', 'VB9', 'VB8', 'VB7', 'VB6', 'VB5', 'VB4', 'VB3', 'VB2', 'VB1', 'AVBR', 'AVBL']\n",
      "c302      >>>  Plotting neuron voltages\n",
      "c302      >>>  Generating plots for: Membrane potentials of 13 neuron(s) (AVB_VB C2)\n",
      "c302      >>>  Plotting muscle voltages\n",
      "c302      >>>  Generating plots for: Membrane potentials of 95 muscle(s) (AVB_VB C2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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JAAuAX0raD7gf2K6w+YK8rCV3d5hZ/4hob+q4+Lg5IraMiB0jYkdSl8Y+EfF7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\nxBykzcxKzEHazKzE/j9vfGY5uEZAoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f564f5ff750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2FqsxJrNkE2vQ9WqQpjjkI0De408DoqrH97ZcRD4FfAj4gKomr3JvACalrDbR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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f564b705cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IjTsIgiJpwKgjaTDwI3yO3VnA3ZKuNLM+VoZ6aZXGPQMfzMfhg3kQBEH70J2z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\nBEHQYfw/KFOWV/CcN9MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f564f634e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AHDKev6o+Ubqoxg91k0UZ5Dmwi6QYYzCsgmGMMWNH2SUYIvIN4ApgDfSdG6l4\nM3uaIbiaQJyRJxiu6xa1gmGDPI0xZmwpuwQDeBtwnKr2lDqQ8ch1k0XuIineIE+rYBhjzNhRNmMw\nMmwGRv4TvEypJos2yNObgbN4gzytgmGMMWNHOVYwuoFVIvIo0FfFUNXrShfS+OEN8hyFMRhqE20Z\nY8zRpBwTjAf8mxkG1VEa5GkVDGOMOaqUXYKhqreKSBSYrarrSx3PeKKa9ibaKsIYjGQySWVlZcZM\nnjYGwxhjjiZlNwZDRC4BVuFdqh0ROVlErKKRh3S6G4BgoGrEbSUSCSoqKqyCYYwxR6mySzCAG4Ez\ngDYAVV0FzC9lQONFKtUJQKAICUZPTw/hcJi+t6CdRWKMMUeVckwwkqraPmCZ/fTNQyrtJxjBYlYw\nBHBsHgxjjDnKlN0YDGC1iFwFBETkGOA64KkSxzQupFNdAAQD1SNqR1X7EgwAkcCIZ/K0CoYxxowt\n5VjB+DjeFVV7gF8C7cAnShrROJFOewlGIDiyBCORSKCqRCIRAESsgmGMMUebckwwLlbVL6jq6f7t\ni8Clo3lAEXmziKwXkY0i8rnRPNZoSiT2A1ARmjiidjo7va6W6movUREJwAgHeVoFwxhjxpZyTDCy\nXTl11K6mKt5pEj8ALgSWAFeKyJLROt5o6knsBaCiYvKI2smWYFgFwxhjji5lMwZDRC4ELgJmiMh3\nM1ZNAEY2jeTgzgA2qupmP447gMvwLrY2riR69uI4YYLBmhG109HRARxKMGDkCYZVMIwxZmwpmwQD\n2A08j9cdsiJjeQfwqVE87gxgR8bjncCrRvF4oybe00Q4PNU/82P4WlpaAJg40etqEXFGPNGW4zik\nUqOZJxpjjClE2SQYqvp34O8i8ktAgGP9VetVNVm6yDwi8mHgwwCzZ88ucTTZdXVtoKpq4Yjb2bdv\nHxMnTux/FolVMIwx5qhSjmMwzgI24I2L+CHwioi8bhSPtwuYlfF4pr+sH1W9RVWXqeqyxsbGUQxn\neFw3QXf3VqoqR5ZgqCo7duxg2rRpfcu8BGPkM3lagmGMMWNH2VQwMvwncEHvdUhE5FjgV8Bpo3S8\n54BjRGQeXmJxBXDVKB1r1LQf/DuqSSbUnjSidvbt28fBgweZP//Q5KmCU5SzSGyQpzHGjB3lmGCE\nMi9ypqqviBTh8qA5qGpKRK4FHgECwE9VdfVoHW+0HNj/BOAwse7VI2rnhRdewHEcjjvuuEMLizAG\nw7pIjDFHGiekAAAgAElEQVRmbCnHBON5Efkx8H/+46vxBn+OGlV9CHhoNI8xmlTTNDffR/3EVxMK\nTRh2O62trTz//PMsXbqUmppDZ6J4E23Zxc6MMeZoUo5jMD6Kd4rodf5tjb/M5LB37++J9+xm+owr\nht1GIpHgN7/5DSLCG97whn7rbJCnMcYcfcqugqGqPSLyfeBRvIucrVfVRInDGrNSqS42bvoW1dWL\nmNz4pmG10dbWxp133snu3bu54oorqK2tHbCFzeRpjDFHm7JLMETkYuBHwCa801Xnicg1qvr70kY2\n9qgq69f/K/H4Lk495XZvSu8Cbdy4kbvvvhvXdbn88stZtGjRYdsUax4M6yIxxpixo+wSDODbwHmq\nuhFARBYAvwMswcigqmzY8FWa99zHvHmfYOLEMwra33Vd/vKXv7B8+XImT57M5ZdfTkNDQ9Zti3Ga\nqlUwjDFmbCnHBKOjN7nwbcabzdP4VF3Wv/Ildu36JbNmvZ95cz9e0P6xWIx77rmHDRs2cMIJJ3DJ\nJZf0TaqVTTFOU7V5MIwxZmwpxwTjeRF5CLgTUOBdwHMi8nYAVb2nlMGVmmqates+T1PTXcyZ8xEW\nzP/ngqYG37NnD3fccQft7e1cdNFFnH766UPvX6TTVK2LxBhjxo5yTDAiwB7gHP/xPiAKXIKXcJRt\nguG6KdauvZ7mPfczb+51zJt3XUHJxdq1a7nnnnsIh8O8733vy3vKc+siMcaYo0/ZJRiq+v5SxzAW\nuW6K1Ws+xd69D7Fg/qeZO/f/FbT/qlWruP/++5k+fTqXX345EybkP1+GNw/G+BjkqaokEvuIxbaT\nTLaRSh0kle4CvK4eEYdAoIpQqJZgsJZgcELffccpu/9uxpgyZp94pl9ysXDBZ5kz58MF7b9y5Uru\nv/9+5s+fzxVXXDHoeItsZAxfrj2ZPMiB1r/S3r6C9vYX6OraQDrdPay2AoFqQqGJhEK1hIJ1BEO1\n/R8HqxEJIk4IRypwnBAiIUS86WoUhb7nqP6SzGUMWKYDlg3YZkB7OdsaQJC+e1n5VS/pt176rctc\nlnW7zF2yrs/cboh2BmzXf9vBY5SszzHfYx++Xc42h3wOBcaWc7vssQkOVVUL+95rxhSDJRhlTlVZ\nu/azXnKx8HPMmf2hw7ZJt7URe/FF4uvXk9y1i2RTE9rVjRuPs6syyqPz5jG9p4dzXnyJ/Xv3smL2\nAp5umMLmSBXdFRWEQyHmRMMsq63inIk1TAkPmJldinMtkmIlGOl0N3v2/I49e39Ha+vfUE3hOGEm\nTDiJadPeRWXlXCqjcwiF6gkGJxAMVgH+V76mSKc6SaUOkky2e/+m2r37yTaSyTaSqTaSyXbiPbtI\nJttJJtvwpmQxpnQaGy/ghON/WFC3qDGDsQSjzG3Z+n2a99zH/Hmf6pdc9GzZwsGHHqLjD3+kZ33f\npVsI1NURnD6NQHUN8UkNPDF5MnXJJGdv3ca9M+bx03mnsLe+gVAyyexNW6jp7qK1spIXGqfyi0gU\nR5XXxg5yVUi5YNokKmbOQCSAq6nDYnO7kySbu0gfTICCU1NBqDFKoDZ82LbF6CKJx3ezfcdPaWq6\ni1Sqg2h0NrNnfYBJjW9gQs0JOE6elZnDwxuUqksq1Uk63YlqCtdN4moSdRP+v2n/V2b/X6feY/+W\nud5f23/Zoe0O7UuWZd5NslQa/GizxK9Z1mvGEu3dcPB2Mpfp4e303h96uyxtDivGYrUz/Oc6dGyF\nHDvb6+f9c+DAX9i1+1e0tv6N+vqzshzHmMKVXYIhIlOArwPTVfVCEVkCvFpVf1Li0I64lpblbNny\nHaZNfTtz534MgO4VK2i55Ra6Hn8CRIieeiqNn/wk0ZNPJrJ0CQH/GiKu63LbbbehO3fypv93Lf/S\nfJC/tHZySk0l/1ZfyTndbQSkiuSuNpI71tLz9J9Ym0jz58kzeOj01/CRynoWrtzI+77yDY477zmk\nJsT2W67BmVCLE52N6lw0OYFspW6nEkJTHMJzQwQmBRAR0vta0HSa7pUrAa+i0VcmHvjvAAm3jV3d\nd9EcexhQGsJnMbX6QmqCi5FuYBv0sC6/F7XQKkqW7R0y5/AP+LfMXQbuk9kdku0YhYWUVdaqvvRf\nNfD1zfZ6H7Ysn30GbuIMXDD0cYY8brYmhmhjWM9vlI4z1HGzbnJoQW3tEvbsfYjdTXdagmGKRspt\n5L2I/B74GfAFVT1JRILASlU9ocSh9Vm2bJk+//yoXn+NROIAzzx7IRWhBk4//V7S+9rZ841/p+P3\nDxNoaGDi1VdR9453EpoyOev+f//737n33nt51cWXcGMqyt5Ekq8eM5OrptUPWmJVVRLt7dy1aQff\nbe9hmwQ5K7GSj3XczPxfL8RpOI9A3bG43ftJ7niadMsGNHYARXEidTi1MwlOWkSgcTESrCDd0URi\nwyM8Xx9j48L5vPOuu/N+DVSU7rNdDl6WRiug8m8O1Q8HCB6wErEpP93/PJWDC/dw9mufIRisGXqH\nMUhEVqjqslLHYTxlV8EAJqnqnSJyA/RdTn1kIwzHoU2bbiKZbOfkk35O91+fY/f11+N2dzPp2mtp\n+OAHcKLRnPumUimWL19O7fQZfDkVpS2V5u6TF3JqbdWQxxURwnV1XH1aHZe7yv/s2MvXNyt1k9/H\n15adSrojQe2b5lF15lmQfjNuRwduTwJNJtBkEk0mIZnE7U7Qsy1Bz5ZpBGreRyS6EdjBrP/9X/oN\nXvT/1czHInTrLrbqrXSyiQksYY5cTfR1U+F12WMuyGhv7+10BI7hG6I0n3WbLPsc9mPmsMdZDz76\nxxm15zeGjpO16nVIfN16Enfdint9ir17H2b69HdlidWYwpRjgtElIg34/8NE5EygvbQhHVmdna+w\nu+kuZs16L+lH19P0+S8QXrCAGd/5L8ILFvTbtifdw9b2rWw9uJUdHTs4ED9Ax4YOnLYADyxaQHMs\nxpnxu/jhIzsIu0EiGiIkQYLBEKFQmIpQhHC0kkhVFdFoDdFQlEgwQiQYIRqIckZFhPMDa/hj6jQ+\nlUow6b2zcGdXk3LShIJhgpFIzudRdZb3YRtfdwDngedpnLCByJmfIRjKnRyl0z1s3fYDtm27hWCo\nmiULv8XUqW+1gW2mrKkqsStfpG3/Spqa7rUEwxRFOSYY/wQ8ACwQkb8CjcA7SxvSkbVl6/cIBCqZ\ntOE4mj53A5WvPpNZ3/8+TpVXgdjSvoWHtzzMM83P8NK+l0i4/sVmFRoTEzir6Vw2TmqgKTyLc579\nHWe88NKgx1MgBnSjJIIuiZCSDLrEK9J0R1zOe/V8/jTpFD469yHan7oLnvL2c8QhEvCTkWCUSCBC\nKBBCEAISwBEHEaFa0rztlFUcE0zwuz+fwx/keNJOBQ4OAQl44xgRJtHCSbxMNV1sZwZrkktJrH0M\n1j7WL95syUa2UwILSUqyn1KYu42sx8t5WujoHTNnLAUmZEWLpcDti3LMAmMpRhtH+vkLwnlXvYHo\n8hdoq3+WeHw3kcj0vNs0JpuySzBU9QUROQc4Du+jeb2qJksc1hETjzexb98jTIteyt7rvkb0tNOY\n9aMfQUWIP2//Mz956Ses3vMSjW1hlqZmc2X8FKKxIMk4xNJCsrKGZLSC52edyOSOVt5TU039u66m\nuqGBikgloUgYRxzS6TRuOkU6lSIRixHv6qS7s53urg5iXR3EuzqJHWynsWsKU5JrmZbeTY+cxEe3\n7SW4YDJuYxU9Exx6AiniqTjxVJxYKkZKU7hu2jtjJOmiyRSnV6zDcVJs3XIyc+a8yHnJ5/jrrvl0\n9wRJp5XqUIyljXuZU9tGR6KCx5rmsaezGmjyXpR+1WLt949weHVZclS6vW31sG17R+1Lxra9/wxc\n5t3NY1yUZAm932PNuVyzfRcpWZdr7xMbgma8UP2OnLHv4bHqYdtAxms4cHm2szEkS8ODxpD9Fcr1\nmmvWP/Yg7Wf+/fv9jXIcN9trftgbLnuMQ71LBv7tNEsbvRLpBHdE49y8fybINpp338fc+YVNtmfM\nQGWXYPjOAObiPf9T/TkUflHakI6M3bvvRNVFvvsigYkTmfm977K5ewc3/vFLtL28keP3TOKUffNJ\nh6tIVdYQr6mjsyIMYe83Um1VFTtPOI32cD2/PHE+r284b9ixuPEUzTc9z+7KzZwdXMVvpl5I53NK\n4IHn+rYJBYJU+eNB3HQKN5UmnUr1TS0eqk4y58o9NG+cxY7mE3jV/rNxT/wBF81cTfeeKIFwmmhD\nD+mk0PxCA3temERd2qGOw0+LLTa/Dw4cB5UA6jjgBNDeM1wyzm5Rr8xC32mjA35lHlqfjWS9m2PB\nkOMxBj9Wzp2yRDVKA8iLMjB9GG3ktUsRYjssvzgyr6O6MX4ybQtXbhJ2pf6POfM+al2HZkTKLsEQ\nkduABcAq6LvClgJHfYKhquzZ+1uqu2ehL+xg2i0380DLY/zfPd/mlHW1hJmLTp1N9zHVuKoEAgFm\nzpzJnDlzmDNnDjNnzqRTArzmmbWcW1PJ6xvynw48m46/7MLtSlIxo4ZzEyu5M3ERoU/8K+8JJtm/\ncxutzU0kurvoicW87+lAkEAwiBMIEqyoIBgK0RN5iLhsJlrzNmhupebAKcyPf4f2qX+gKrqZQKCS\n6ujJ1E94M8FFdfAPGadW9p5mKb3zP2T8k7Gs7zN2wFwUIt7puvv2H6Bl/35a29pobWunq7uLrq5u\nuru7SafLbvywGa9UmdY6gY5X/kZkwR7a9j/LxEmvKnVUZhwruwQDWAYs0XI7Pxfo6tpAd/dm6h6p\novr887k9/CJrv3cPZ7ZPx51zDN2BCiKRCKcsXcrSpUuZPXs26gRY1xXjrwe7WbW5mccPHKQzleZL\nDUlofglSCUgnwPUrAr1fzFn+VRfcHiHdDal26HwiTnRhkIATZ4q7i7MqHe7YuYdPHBel4ZhpcOx0\nEMff3xlwE9Ka5MkXvszkuvOpcJbAhr8SaKggunsqC9/8bwOe/RC/xAb9pdZ/XXd3jDXrX2HdKxvY\nvnMXiYTXw+Y4DvUT66ipqaZxUgPVVVVEo1FCoRAVFSEqQiEqKioIBoI4juAEAogjOOLgON5NRPz7\ngvhjTA6FmHnf6Rtb0hviYfclSzLlBdpv7orD78uh+9nmWxj4yzfb65RtG8m9njxnYh1qm2K0UY7H\nSaVS/OGhh9gowgtdwms6lrP+yc9x5luXD9m2MbmUY4LxMjCVvg748tHS8igA4WcSPPvZWey8+UEm\nR+cTWzCTSCTKm173OhadcDzP7XqFH+/awMotm1kjdfSI9zapT7ZzUsc6btp5F4sff7avXVUHlzrS\nWu/fGrx/qcfVetI6kbROxKWOzEmjHPZTu/169lR2QV2Iq7b+G9cu/iJP3v4RXte2Ysjns7+hgtTS\nCUx/7C7aWzcAZxNt/ymx/e8h9fUzCDrNh+3jInQHInQEqugKROkKROkMVNIViNLtP868Za5rDUyg\nOTCJ9kANKSeAM2k+gUlzcMRFRFGEtDi44njdDAAJIKHQlfAfdOUseecshedYPFjpvNBj5BhqUHg7\nBbY/2D65nvjh2/tpUY4v0cFjzTVocoTPrzfXyxlTdoW+FsNpK9vfIugIixYvYnqkisQ62LbzGGYv\n3kDTM7cx7VXvznlsYwZTjhNtLQdOBp4FenqXq+qlJQtqgNGaaGvlqvfTsf5v1D14IndG2olMOJbU\nhAaWLF7MlPnV/LrlIL+rWECPU0FlupuTOzdyYrKVpa7DCUmHGakorltLOhkl3RMiHQvixhzcHsky\nWk2RiHcLRBUn4uJUevcDlS7BqBKelMIJwpq2X3KgZx3LGv6FMw/MYq6T5N4JOxBc0N6bZtz3bi/G\n7qXd3clrItfw160x7tgV4IST57Jx+3RaGxMcnJCmUwN0EqBTA3QQoIvAoS//IYRxqSJNJWlIJEnG\nk4TSKRorXBojQlUQAgqOK4gLjvqP1f8QV/zXRfxrj+X59dFvwGf2WAf7X5tzwGLOtnK1dvjftN+x\npf8qr/3DBygO5xOm0K/ZnMtz/Klz5ANDvK7Ztzj8dc21ZWEx5aNYr1M80cWqqkbaQ5UsiLWzeOOL\nvHXe/xLtiXPK0l9Sv3h8zF1lE22NLeVYwbix1AGUguumaD/wLOG1aR6sbCcSXUhqQgMLj5/FPaEe\nHus8jgnBOq6I7+S8nloW767G2bcQ6Tk0hqAdr9TaoxB3lbhC3HWJu+lDt3SamJsmrml6RImLEgdS\nfd+4foKAS1DTVJBixklKw0yHH9+2lpOPaefhV53MtXfvYNG2V1A3gbo9uG6Pf8VV7yPSCaVY9O6N\nPLPj1Xw1EWX9vNOIT41wN1Ax26UxHiDU0kGlm6LWTTPVhajrEk27RFIu0bQSdl0iaW9Z2FUiaZdw\nWom4LmHXJegKaTfF2vQ2Oogxx23kZHceNW6EoAYI6MDrfxgzXoWJO2numxnntnmV/PaEs3m+6zje\nPvF2WlZ8kppnL+aCd3+GoFOOXxlmuMqugjEejEYFo6NjNc8+dynOndU8rafQM20uyQX13D7tVYRJ\n85HuNBe/HKLyoDeeoCOdpi3ZycF0C02pJva5HbS6cTrdFHGC9DgheiRMPBAm7kTocSJ99+OBCHEn\njBZ46eegm2RC6iAHGxtI1YQ5beMKpnbupcaNE9Y0IdI4wP6J9Ww+eQ5rZi6mXSYSSiaY17SdWZ2t\nzF69kkWxCs6f8g5W7n+UVw56r6NKgHQghCtBXCeIK34lQwQXp++XXXWglimRGTQEJ1MRqeWJ8HoS\nuJyZPJa6VJTudDfdrnfrcRMkNUnKTZLUBGlN4aqLq2kUF1UXxTul1iVN7yXSRQdcGn3AJdjpXd93\n39M/lRlQPshiOKlP1hrLYRdSG0j9faVfNPkeP9usDAM5+bQqA1+hXK9LrjY05zaDPcrcWzK2yF0V\nyfKMJduWvSNiMsbP5Ih34H4Dtx3qNRaUoISZHJlGQ2Q2K+bM4o45YZorHUKSYqG7kYbmJDNbupjs\npDl53nROPn4pk2bPJhiK4jhj4zLvVsEYW8ouwfBn7vwesBiowBsU0KWqIzsloohGI8HY3XQPa9d+\nhnV3LWRv46vYtGAOf5p1Gq+JdfHF56Ax5rI21c6TyQeYEAhQEasglAwTSFUibjVCBUgIJQxSgRLo\nHTGI9/E0YFAnuUvy2YzOqXglbDPvQ+cf4/h4jQppr3SvZf4K+fsUu81ReD6j8nlf3OfTNOUp/uU/\nbhlWJJZgjC3lWO/6PnAF8Bu8M0reAxxb0oiOgI6dz0EKDlYdw8uzFvDXWSdx2Z4eLnrsFZZHn6O6\nbRKOHsvkyBV9+6SDADEC6YPg9iCaQOgGbQdJIa4/EZEqcmjQgb935v2hlLKboZBjFzvOEnev5BoM\nMNAozIUgeRy7oK/CvGPUvI9dSPdX/u/00fibj4f3ZQFtpt1ROL4phXJMMFDVjSISUK9T/2cishK4\nodRxjaaOlhfp6QqzecYinpp/Aic99jKLD/yNfbFXEeadpEJJwvFNBBOriVd2EK9KI6EKrv/qf496\nbK9s+Cq7d/+Gc8/5+2HrtsV62NzdQ1XA4ZiqCBNDQTq7NvDMM29m0XFfY8YMLyFasWIFDz74IJ/6\n1Keora0FoGf7QVp+thpNpIkuricwMYLblSSxo4PUvhgAFXMnUHlSI9HjJxGoqQBg+fLlPP7447z9\n7W/nxBNPHPXnb8x4oerS3b2Frq4NJBL7SaU6wPVm1EUFxwkTcMI4UoETrCQQqsQJRQmGqggEK3Gc\nsLdNIILjRHCcCkQCQx/YjEvlmGB0i0gFsEpE/gPvdNWx0YE4irpSOziYmMTjx57Mx35/C9P2LCZe\n+Q5UmkEfpL2+mxu+cXNJYhMcfwDn4eZEw8yJhvsta2t9BoD6+rMOteH/gs3s8gvPnsDUT53KweU7\niK89QHpdK05lkIrp1VSdMZXoCZMI1vW/mFpLSwtPPvkkJ5xwgiUXxgwg4lBVtYCqqgVDb2zKXjkm\nGO/GSyiuBT4FzALeUdKIRlk63UMy2sWDyQ/wwcdup77l9fRE6nBSDxE/LszHb/ivksbn/YLJf8bL\ntvYVVFRMJhKZldHG4QkGQGBCmImXLYTL8mv7kUceIRgMcsEFF+QdjzHGmMOVVYIh3jfZ11X1aiAO\nfLnEIR0RXa1rSToVHP/MOibuO590IEKs+l4+/Z//U+rQPBLou7ZIPtrbV1BXe1q/mS17R7G77vD7\nb3fu3MmGDRs4//zzqampGXY7xhhjyqBrIJM/5mKO30VSNlo3LGf50ycxuflU0sFqOuseGjvJBV7Z\nNd8EIx5vIh7fRW3daQPayF7BKMQTTzxBNBrljDPOGHYbxhhjPGVVwfBtBv4qIg8AXb0LVfU/SxfS\n6Nq24bfM33Qa8ehCXOc+/vlbYye5AG8MBrio6pBXb2xv96YQr6stboLR0tLCK6+8wrnnnks4HB56\nB2OMMYMqxwRjk39zgLKog//t5WOY4JxHpHsVH/zFd0sdzuH6RpG7ZF6rJJv2g3/HccJUVy/ut3yk\nXSQvvPACIsJpp5029MbGGGOGVHYJhqp+GUBEJngPtaPEIY0qTSVp2DOLZIXQMmVjqcPJSvwZP1XT\nQ56y1tGxmurqRThOaEAbw69gpFIpVq1axXHHHWdjL4wxpkjKagwGgIgsE5GXgBeBl0Tk7yJy1P5s\n/Y8vfJxE+HSCyWf57E0/LHU4WYlftRhqHIaq0tm5lprqJYet661gDCfB2LhxI93d3Zx66qkF72uM\nMSa7skswgJ8C/09V56rqXOBjwM9KG9Lombh3EioOBxrH7tXpMysYg4nHd5FKHaS65vAEo7eCMZwu\nkjVr1hCJRFiwwM7tN8aYYim7LhIgrap/6X2gqk+KSKqUAY2WH3zrS4TkVCKx1Xzs5rE1sDOT9BuD\nkVtH52qArBWM4XaRpFIp1q9fz+LFiwkEbEZBY4wplrKpYIjIqSJyKvC4iNwsIueKyDki8kPgsRG2\nfZOIrBORF0XkXhGpy1h3g4hsFJH1IvKmET6NgiR27CNZUUfXhA1H8rCF66tgDJFgdKwBHKqrjzts\n3XAHeW7ZsoWenh4WL1489MbGGGPyVk4VjG8PePyljPsjvcTgH4EbVDUlIt/Eu67JZ0VkCd6F1ZYC\n04E/icixOlRfQJHUtM0mFepmf23iSBxu2IT8ukg6O9dSVbWAQCB6eBvDrGCsX7+eUCjE/PnzC9rP\nGGPM4MomwVDV80ax7T9kPHwaeKd//zLgDlXtAbaIyEbgDOBvoxVLr5//+Hukg4sJJtfwr98c3qWP\nj5TeLhIdoouks3MdtbXZB2ION8HYvHkzc+fOJRQKDb2xMcaYvJVNgtHL7754DzCXjOevqtcV6RAf\nAH7t35+Bl3D02ukvG3Uta9cSDS0lEd55JA43Mn4XCYNUMNLpbuLxXUyf9q6s64fTRdLW1saBAwc4\n/fTT84/VGGNMXsouwQAewvvSf4mhRhVmEJE/AVOzrPqCqt7vb/MFIAXcXmhQIvJh4MMAs2fPLnT3\nw9S01pIKuXRUJ0fc1mjrq2AMkmB0d28BoLJqYY42Cq9gbN68GcDOHjHGmFFQjglGRFX/qdCdVPUN\ng60XkfcBbwHO10Pfcrvwrtbaa6a/LFv7twC3ACxbtmykY0IIpuYRSG/n82P47JFe+cyD0dW1CYCq\nyuzJwHDmwdi8eTPV1dU0NjbmvY8xxpj8lM1ZJBluE5EPicg0EanvvY2kQRF5M3A9cKmqdmesegC4\nQkTCIjIPOAZ4diTHysfXP/NReiJzUNk22ocqinzmwejq3gg4VFbOydFGYfNgqCpbt25l3rx5Q17/\nxBhjTOHKsYKRAG4CvsChs0cUGMlpBN8HwsAf/S+rp1X1I6q6WkTuBNbgdZ187EicQRJOC+qE6K7e\nP9qHKo7eMRiD9Fh1dW0iGp2N42S/EFmhXSRtbW10dnYya9asoTc2xhhTsHJMMD4NLFTVlmI1qKrZ\nBwZ4674GfK1Yx8pH5cEq3CD0jIPxF5B5mmruBKO7exNVOcZfQOGDPHfu9Aa/WoJhjDGjoxy7SDYC\n3UNuNY5VJKZR0bOP679xc6lDyctQgzxdN0V399ac4y+8NgqrYOzYsYNQKMTkyZMLjNYYY0w+yrGC\n0QWsEpHlQE/vwiKeplpybmAmTnp7qcPI21DzYMTjO1BNUlmVuxer0ARj586dTJ8+3aYHN8aYUVKO\nCcZ9/u2o9JXPXkN9+HICyRWlDiVvMsQ8GEOdQQKFdZEkk0mam5s566yzCozUGGNMvsouwVDVW0Uk\nCsxW1fWljqfYqpLeF228qrPEkRRgiC6SWMw7G6aycm7uJgqoYDQ1NeG6LjNnziwwUGOMMfkquzEY\nInIJsAp42H98sog8UNqoiifcFQGgJ3JELndSFH2DPHNcEiYW20EwWEMwWJd1PRSeYABMnz690FCN\nMcbkqewSDOBGvOuBtAGo6ipGdorqmBLuqSeQ6ubEU95Y6lDyNlQXSSy2jWh09qDzVRTSRdLc3Exl\nZSU1NTWFB2uMMSYv5ZhgJFW1fcCywq7xPYaJO4VQYjcXXvmOUoeSPxl8Js/u2HaikcGnTy+kgtHc\n3MzUqVNtgi1jjBlF5ZhgrBaRq4CAiBwjIt8Dnip1UMWSCk1GZV+pwyiII96VTF09fN4O1TTx+C6i\n0cETjHynCk+n0+zdu5epU7NdVsYYY0yxlGOC8XFgKd4pqr8CDgKfLGlERfKVz15DKjSBVGhggWZs\ncxwvwVD38AQjHm9CNTlkgpHvVOEtLS2k02lLMIwxZpSV41kk3XjThH+h1LEUWzTt5Ys9kfE1j5gM\nUsGIxbz5PPJNMIaqYDQ3NwNYgmGMMaOsbBKMoc4UUdVLj1Qso6Ui5v05E+PoDBIAGaSCkW+Cke8g\nzz179hAIBGhoaBhOqMYYY/JUNgkG8GpgB163yDPAUTfCLxyvIhWCeJZKwFjWNwbDTRy2LhbbjkiI\nSE2VtIwAACAASURBVGTa4G3kmWA0NzczZcoUm8HTGGNGWTklGFOBNwJXAlcBvwN+paqrSxpVEQVS\ndYi28i8/+nGpQylI3xiMHF0kkciMvunEc+lNGNLpwas3e/bs4ZhjjhlmpMYYY/JVNoM8VTWtqg+r\n6nuBM/EuevaYiFxb4tCKRmggkC7aRWKPmENjMFKHrYvFt1M5RPcI5JdgxGIxurq6aGxsHGakxhhj\n8lVOFQxEJAxcjFfFmAt8F7i3lDEVUzK4ETcwvrpHIPdZJKpKLLad2gmn5tGGg4gMmmDs2+edvmsJ\nhjHGjL6ySTBE5BfA8cBDwJdV9eUSh1R0H/nJN0sdwrCIVACHn0WSSrWRSnUQjc7Kq51AIDDoGIyW\nFq+6M2nSpGFGaowxJl9lk2AA/4h3qfZPANdlzOIogKrqhFIFVu4OVTD6D/LszvMMkkPtOENWMILB\nIHV1ua9pYowxpjjKJsFQ1bIZbzLe9I3BGNBFku8pqr0CgcCQCUZDQ0PfGSfGGGNGj33SmpLzzhCR\nw7pIip1gtLS02PgLY4w5QizBMCUnIjhO6LBBnrHYdioqGgkEonm1M9gYjEQiQVtbmyUYxhhzhFiC\nYcYEkYosFYwdeVcvYPAxGDbA0xhjjixLMMyYkKuCUUiCMVgXSW+CYRUMY4w5MizBMGOCSBBXD51F\n4ro99PQ0Fy3B2LdvHyJCfX39iGM1xhgzNEswzJjgSP8KRiy2C1CikfzmwIChE4z6+nqCwbI5ccoY\nY0rKEgwzJogT6jcGIxbvPYOksAQj1yBPO4PEGGOOLEswzJjgOBX/P3vnHt9ElTb+Z3JPmqRNk5Zy\nE7CViwrri7wI3qrQQiGUYrUCqx8uvy26qPByEUUQcUEooEBfiigXKQvLZcUL1IYWyiJdVC4WUGT3\nbREE5N5m2rRN0+Y6vz+aYUtML+mcSSb4fD8fPjSTaXLm6cmZZ86ZPN87bKr19VcAoO1fUW18Df83\nebrdbqisrMQbPBEEQYIIJhiIIBCLlOBx199+3FB/BUQiOchkbZ91aG6JxGKxgMfjAb1eT6StCIIg\nSOtggoEIApFYCe4mCQb7DZImJd1bpbkEg/0GCSYYCIIgwQMTDEQQiMUqcLtttx/XN1wJ6AbPxtfw\nn2DQNA0AWAMDQRAkmGCCgQgCsVgJbk9jgtGoab8CigBu8Gx8Df83edI0DUqlElQqFZG2IgiCIK2D\nCQYiCBpnMBqXSJzOSnC760AVwA2eAM3f5Gk2m3F5BEEQJMhggoEIgqZLJO35BgkAgEQiAZfL9Zvt\nNE3j8giCIEiQwQQDEQR3JhiNNTAUii4BvYZUKgWn885y4w0NDWC1WnEGA0EQJMhggoEIArFICQzj\nAo/HATbbRQAQgVLZLaDX8JdgsDd4YoKBIAgSXDDBQASBWNx4A6bbXQ91tgugVHYBsVge0GtIpVJw\nu9133OiJ3yBBEAQJDZhgIIJAItEAAIDLVQM22y+gUt0b8GtIpVIAgDtmMWiaRskZgiBICMAEAxEE\nMlnjEobDYQab7ReIUMUH/Br+Egyz2QxRUVEoOUMQBAkymGAggkDqTTBqan8Cj8dOdAYD779AEAQJ\nPphgEISiqNkURTEURRm8jymKotZQFHWeoqgzFEX1D3UbhYpM2niPBE3/EwAA1OpeAb+Gb4LBMAwm\nGAiCICECEwxCUBTVFQCGAcCvTTaPAID7vP9eAoCPQtC0sIBdIqHpr4GiJKBW39+O15ABAIDD0Whl\nrampAafTiTd4IgiChABMMMixGgDeAACmybY0ANjKNHIMAKIoiuoYktYJHLFYAQpFZwAAUKt7B/wN\nEoDfzmDgV1QRBEFCByYYBKAoKg0ArjEM86PPU50B4EqTx1e92xA/aDR9AQDAoB/Srt/3TTDKy8sB\nACAmpu3KdwRBEIQMeGt9G6Eo6iAAxPl5aj4AzIPG5REur/8SNC6jwD33BFYi+24hIf51UCg6wT33\n/L92/b7vEklFRQUolUpQq9XE2oggCIK0DUww2gjDMEn+tlMU1RcAegDAjxRFAQB0AYBTFEUNBIBr\nANBUCdrFu83f628AgA0AAAMGDGD87XO3o1L1gJ73zW/37yuVSgAAqK9vlKaVl5dDbGwseP8uCIIg\nSBDBJRKOMAzzE8MwsQzDdGcYpjs0LoP0ZxjmJgDkAcAE77dJBgFANcMwN0LZ3rsZNsGw2WzAMAyU\nl5fj8giCIEiIwBkMftkHACMB4DwA2ABgcmibc3cjkUhAJpNBfX091NTUgN1uh9jY2FA3C0EQ5HcJ\nJhiE8c5isD8zAPBq6Frz+0OpVILNZrt9gycmGAiCIKEBl0iQuwqVSgU2mw2uXWu81SUuzt99uQiC\nIAjfYIKB3FVoNBqoqamBa9euQUxMDCgUilA3CUEQ5HcJJhjIXYVerwez2Qy//vordOnSJdTNQRAE\n+d2CCQZyV2EwGMDj8YDdboeEhIRQNwdBEOR3CyYYyF0Fm1QoFApMMBAEQUIIfosEuauIjIyEzMxM\nkMvlIJcH7jNBEARByIAJBnLXgfdeIAiChB5cIkEQBEEQhDiYYCAIgiAIQhxMMBAEQRAEIQ4mGAiC\nIAiCEAcTDARBEARBiIMJBoIgCIIgxMEEA0EQBEEQ4mCCgSAIgiAIcSiGYULdBsQHiqIqAOByO3/d\nAABmgs0hBbYrMLBdgYHtCoy7tV3dGIaJIdUYhBuYYNxlUBRVwjDMgFC3wxdsV2BguwID2xUY2C4k\nGOASCYIgCIIgxMEEA0EQBEEQ4mCCcfexIdQNaAZsV2BguwID2xUY2C6Ed/AeDARBEARBiIMzGAiC\nIAiCEAcTjLsEiqJSKIoqoyjqPEVRc0Pw/pcoivqJoqgfKIoq8W6LpiiqiKKon73/67zbKYqi1njb\neoaiqP6E27KZoqhyiqLONtkWcFsoipro3f9niqIm8tSudymKuuaN2w8URY1s8txb3naVURQ1vMl2\nYn9riqK6UhT1NUVR/6Yo6l8URf2Pd3tI49VCu0IdLwVFUScoivrR266/eLf3oCjquPc9/k5RlMy7\nXe59fN77fPfW2ku4XVsoirrYJF4PebcHrd97X1NMUdRpiqLyvY9DGi8kSDAMg//C/B8AiAHgAgDc\nCwAyAPgRAO4PchsuAYDBZ9sKAJjr/XkuACz3/jwSAAoAgAKAQQBwnHBbngSA/gBwtr1tAYBoAPjF\n+7/O+7OOh3a9CwCv+9n3fu/fUQ4APbx/XzHpvzUAdASA/t6fNQBwzvveIY1XC+0KdbwoAFB7f5YC\nwHFvHD4FgHHe7R8DwFTvz68AwMfen8cBwN9bai8P7doCAM/52T9o/d77urMAYAcA5HsfhzRe+C84\n/3AG4+5gIACcZxjmF4ZhHACwCwDSQtwmgMY2/NX7818BYEyT7VuZRo4BQBRFUR1JvSnDMP8EgEqO\nbRkOAEUMw1QyDFMFAEUAkMJDu5ojDQB2MQxjZxjmIgCch8a/M9G/NcMwNxiGOeX9uRYA/g8AOkOI\n49VCu5ojWPFiGIaxeh9Kvf8YABgCAJ95t/vGi43jZwAwlKIoqoX2km5XcwSt31MU1QUAjACwyfuY\nghDHCwkOmGDcHXQGgCtNHl+FlgdjPmAA4ABFUScpinrJu60DwzA3vD/fBIAO3p9D0d5A2xLMNr7m\nnabezC5FhKJd3uno/4LGq1/BxMunXQAhjpd3uv8HACiHxhPwBQCwMAzj8vMet9/f+3w1AOiD0S6G\nYdh4LfHGazVFUXLfdvm8Px9/x2wAeAMAPN7HehBAvBD+wQQDIcXjDMP0B4ARAPAqRVFPNn2SYRgG\nWr6iChpCagsAfAQA8QDwEADcAICVoWgERVFqAPgcAGYwDFPT9LlQxstPu0IeL4Zh3AzDPAQAXaDx\nKrp3sNvgD992URT1IAC8BY3t+29oXPZ4M5htoihqFACUMwxzMpjviwgDTDDuDq4BQNcmj7t4twUN\nhmGuef8vB4AvoXHgvcUufXj/L/fuHor2BtqWoLSRYZhb3hODBwA2wn+mfYPWLoqipNB4Et/OMMwX\n3s0hj5e/dgkhXiwMw1gA4GsAGAyNSwwSP+9x+/29z0cCAB2kdqV4l5oYhmHsAJALwY/XYwAwmqKo\nS9C4PDUEAP4XBBQvhD8wwbg7+B4A7vPemS2Dxpuj8oL15hRFRVAUpWF/BoBhAHDW2wb2LvSJALDX\n+3MeAEzw3sk+CACqm0zH80WgbdkPAMMoitJ5p+GHebcRxefek2egMW5su8Z576rvAQD3AcAJIPy3\n9q5vfwIA/8cwzKomT4U0Xs21SwDxiqEoKsr7sxIAkqHx/pCvAeA5726+8WLj+BwAHPLOCDXXXpLt\nKm2SJFLQeJ9D03jx/ndkGOYthmG6MAzTHRpjf4hhmBcgxPFCgkOLhbZOnjwZK5FINgHAg4DJiKBp\naGhQ1tTURAMAKJVKq0ajqQ7We7tcLklVVVUs+1ihUNRpNJpqj8cjqqqqinG73RKxWOzS6XQVIpHI\nAwBgsViiHQ6HkqIoJjIykpbJZHZS7amqqopxOBxyj8cjFolEbrVabVEqlbZA22Kz2dRWqzUSAECt\nVlerVCprS+/bnnY5HA6Fy+WSAQCIxWJXZGQkLRaL3QAAtbW1kfX19WoAAK1WW6lQKOoByP6tHQ6H\ngqbpDhKJxMlu02g0VTKZzB7KeDXXrvr6+ohQxsvpdMosFoseGr99cbuvu1wuicViifF4PCKJROLQ\n6XRmiqIYhmGoqqoqg8vlkolEIk9UVFSFRCJxtdReku2iabqDx+MRAwBIJBJHVFRUJUVRQe33LHa7\nXWG1WrV6vb481PFCiOABgLMulyvz4YcfLve3Q4sJxo8//pgXFxfXJyYmpgYAgGEYip92IgiCIAgS\nLng8HjCbzZE3b94sXbhw4ai8vLzfJBMSf7/YhAcNBkOV1WqNrKuriwLh3BiHIAiCIEgIYRgG6uvr\nnwSA2aNHj/4wLy/vjlml1hIMkcfjkdTV1UVJJBIHf81EEARBECTcEIvFUgD4AwAMAIAjTZ9r9b4K\nj8cjoiiK95mLw4cPyzp27Njx1q1bIgCA77//XhobG9sxISEhzu12397vj3/8o+7SpUvigQMHxo4a\nNUqfnJxs+Oqrr+QAAPn5+fLk5GRDcnKyITs7OwIA4OzZs5Jhw4YZRowYof/zn/8c5fF4/L6/UCAR\nh9OnT0see+yxmIceeuj2fRH+tgmZQOOQkpKib/r7mzZtUrF9YefOnUoAgAMHDshTUlL0ycnJhnff\nfVcT1ANqJ1zjUFhYKH/kkUdimm73ty0caC4WW7duVQ4cODB29OjR+tGjR+uLiork7P5/+MMfYkeN\nGqUfM2ZMtNlspgAApk+fHjl8+HBDSkqK/syZMxIAgA8++EBtNBr1Q4YMMezZs0cRuqNsG6RisXz5\ncvUDDzzQ4S9/+cvtz4O/bUKmPbHwPbaxY8dGjxgxQj969Gj9lStXRAAAc+bM0RqNRn1SUpLh22+/\nlQb/yAKDRBxmzJgR2atXrw6bN29WtbTNDw5o/MbPHQjqxs3evXs78/PzFQAA+fn5igcffND50EMP\nOY4ePSoDAKirq6MqKytF3bt3d0dHR7vz8/PpvXv3mjds2KAGAOjbt6+roKDAvH//fnNRUZHCYrFQ\nPXv2dB04cMBcUFBAAwCcPHlS8B2Faxzi4+Pd+/fvN8fFxd0+A/nbJnQCiYPv7w4dOtReVFRkNplM\n5vXr10cAADz11FP2wsJCuqioyFxSUiIrLy8XVP9vDi5xGDhwoKO4uLiitW3hgr9YAAD8+c9/tubl\n5dFbtmypXLVqlfratWsiAID09PT6/Px8+vnnn6/fvXu3EgBgxowZ1v3795vXrFljWbFihQYAYPr0\n6VaTyUTv3buX/vDDD9WhOr5AIBGLiRMn2tauXVvV9HX9bRM6gcbCl6ysrOqCggJ62rRpVvbvv2TJ\nkhqTyURv2rSpKjs7OyySLa5xeOONN2rnz59f09q2tiKoAfbRRx91HDlyRA4AUFZWJrnvvvtcI0eO\nbDCZTAqAxivQp5566o5vG1itVpHL1VgQrlu3bm6JRAIikQjEYjGIRCKQyWS395XL5UyXLl0Ef4Ll\nGgetVsuo1eo7Zp38bRM67YkDS48ePdwAABKJBCSSxpVAti+4XC6IiYlxa7VaYU9neeESh+joaEah\nULS6LVzwF4umz0dHRzPjxo2zHTp0SN50e3V19e0b1O+99143AIBUKgWxWAwA/+kb9fX1VM+ePZ0Q\nBpCIRVxcnKfxG6z/wd82odPeWLA06ROMb5+oq6uj7r///ru6T7B06tTpN2Oiv21tpbV7MAAA4P1D\nv0b8bK4Xt/dNAADui1E55yZ1bzELkslkjFwuZ44dOya97777XOXl5eInnnjCvmPHDhUAwL59+xQz\nZsywAgBUVlaKjUajvqysTJqTk3NHtl1YWCjv1q2bS6vVMgAAX331lTwrK0vbvXt3l16v53RSyT6b\nrb1Qe4HTLEi8Jt4548EZzcaCVBz45GTeNa3lVgOnOER1UDgfHt2ZSByaY+PGjaphw4Y1sI83bdqk\n+uijj9SJiYl2EidZ58GbWqbCzikOVIzcKU2K4xwHj8dDMQwjpWk6xu12iyiKAvarpQzDcPr8NofT\n6ZTYbLaIyMjI6qvXVmgbGs63KxYeDyMGAEalus/epfMbAcXCd5+4uDjPTz/9JO3atav7iy++UB4+\nfFje0NBAFRQUmJvut2jRIs2UKVPq2MczZsyIPHDggGLBggXtulpryrKDl7Q/V9g49YvWxkySseCT\nUI2Zvvs0jYW/13C5XLB69WrNypUrLey2P/7xj7ozZ87I1qxZw3lsDdWY6btPa3EgiaBmMAAAkpKS\nGt54442o1NTUBoDGK9D4+HjX6dOnJRcvXpQ88MADLgCA6Ohot8lkoj/++OPKb7755nY2duHCBfHa\ntWvVWVlZt/8Iqamp9u+++66iY8eO7n379oXFpRvXONwttDUO/jh+/Lj00KFDilmzZt1OQjIzM20n\nTpwov3Hjhuj06dNtSrCFQFviIBKJGIqinHq9vkKlUtlUKpVVr9dX6PX6CoqieLkCq6ur00RERNS1\nvmfLiESU25tktIpvLHy5ceOGiF0KTE9Pr//666/N/fr1c165cuX26+fk5ET07NnT9fjjj9++eT07\nO7v6u+++K1+zZk1YLJEAkInF3UIgsfDHvHnztBkZGbaEhITb++zYsaOqoKCgIisrS8tHm/mAaxxI\n0qYBds6Qe+rEYnFQpohSUlLsX3/9tXzAgAHOTz75BAAAjEZjw9tvvx05aNCg30wDJyUlOdasWaOp\nrKykJBIJTJs2LSonJ8fCLgc0NDQAe6Wq0WgYpVLJaZmgpSyaJFziEB0dzftSSEtZNEkCjQPL1atX\nRQsXLtRu3769kl0iYfuCWCwGlUrFKJVKzu1raeaBJO2NAwvDMDIAAIfDIbNarRqKojwMw8hqa2s1\nEonEZbPZIhiGoXQ6XaVYLHZ7PB5RTU1NpNvtFgMAaDSaaplM5vR5TcrlcknYQkhRka8wbrXb7Xa7\nxW63W6zRaGqcTqfMbrfLxWKxW6fTVQIA1NbWaux2uwIAQC6X2zUaTQ0AQFVVlU6tVrdaPMlfLFiq\nqqqo3bt3qzZu3Fh17ty52+PbzJkza5cvX67Jzc21HDhwQF5SUiLLzc29fVXK9g2lUklkKbG12VpS\ncI1FMNoYyjGTpblYsOTm5qooioIXX3zxdv9j+4RareZ83gAI7ZjJ0locSCO4KziNRsOsW7fujkp7\nycnJDdOmTYtqbuoyPT3dtm3bNpXD4aCuXr0qmT59ehQAQE5OjuXs2bNS9ia/7t27u5KSkohVjOQT\nLnF45pln6qdNm6b7+eefpWlpafrs7GyLWCxmfLex9ykImbbGoaqqSpSWlqYHAPjDH/7gsFgsIrPZ\nLJ4wYUI0AMDu3bvpv/3tb6q9e/cqPR4PDB482NG7d+9mZz+ERqBxYBhG3K9fP9eYMWMcixcv1p4/\nfx7S0tL027Ztq/3hhx+k//u//+s8f/4888ILL6g3b95sNRgM5rq6uoi6uroIrVZbU1NTo1WpVHUy\nmczhdrvFVVVV0QaD4Y4bQ51Op5RNLljcbrc4OjqadrlcEpqmDVFRUVUajaamqqpK19DQoJDJZHa7\n3a5gX6tp8T6pVOp0OBwyqVTa4sWMv1h8/PHH6j179ty+ibNTp06ec+fO3X6+d+/e7srKSvGNGzdE\nb7/9dqRarfakpqbq4+PjXWvWrKl+8803I8+fPy9xOp3UK6+8QqRyZTDgGovCwkLFX//6V1V1dbXI\nYrGIVq9eXZ2bm6vy3Rbkw2oXgcRiz549ylOnTskAGhOut99+O7Jfv34Oo9GoHzRokGPBggW1kydP\n1tXU1Ig8Hg/Mnz+/NhTH1B64xOH48eMydr+bN2+K5s2bZ12+fLnad1tb29JaJc9LvXv3rq2qqooL\n1gwGgiDcYWcp2OWLW7duxXXo0OGmdwZDHR0dXQkAUFlZqVer1TUymczpcDhkdXV1ETqdrqq8vLyD\nWCy+fb+Sx+MRGQyG8qZfWa+vr1c6nU6ZVqutZt8TABi1Wm31vmfHDh063PBtD03TMRKJxCmXyxsU\nCsXtaVybzaZyu90SdkYDQRDh88svv6iWLFnyOQB8mZeXl9/0OcHNYCAIwi++3xDweXz7QXR0dEVL\n3yZg3RG+25o89Hv1otfrK+x2u7yhoUFps9kioqOj6dZ+B0GQ8ENwN3kiCBJ6ZDKZ3WazRbCPnU7n\nby5GJBKJi71Ho60wDEN5PB6RXC63a7XaapfLdft1XS6XpLXlEQRBwgecwUAQ5Dd478OINJvNKgAA\nmUzmkEqld6zrSiQSl8fjETEMQ7W12q/XlhnNznw0XQ5xOp0ytVodNmvdCIK0DCYYCHIX4nui7tCh\nw02AxkRBJpNVstubLk80fc6rym71u/9KpdJWX1+vVKlUtube07c9er3+NzUYnE6nRCKRuEQiES6R\nIMhdAi6RIAjSblQqVR0JV5HH4xHh7AWC3F0IJsHgS3Z2/Phx6bBhwwwpKSn6N998U/DFUviSnTmd\nTpgyZUpUSkqK/oMPPhB8ISE+ZGf++ofQ4UN2VlNTQ40dOzZ6+PDhhr/97W+cioFQFAVKpbLV2hWt\nIZfLHWKxuMWvTfMpO1uyZIma7Rv/+Mc/ZM23QhjwKTs7e/asJCUlRT98+HADGx8hw5fszF8/ETJ8\nyc4OHTokS05ONowaNep2bNqKYBIMAH5kZ/fcc49779695sLCQtpsNot++uknwXcUPmRn+fn5ioSE\nBFdhYSF94sQJ2Y0bNwT1t/cHadmZv/4R3CNqH6RlZ7m5uaq0tLR6k8lk3rFjh8puD4vSMADAn+xs\n/Pjx9UVFReZPP/2UXrly5V0ptmqr7Gzp0qWaDRs2VH3yySeVS5cuvStj4Ys/2Zm/fiJ0+JCdrVq1\nSvP555/TCxYsqFm1alVAcRDUSYYP2VnHjh09bMVGiURyW24kZPiQnZWUlMiefvppu/f17SUlJYK3\nypKWnfnrH+EAadnZqVOnZEOHDrVLJBLo06ePs6ysTPBJNwtfsjN2m1wuZ8JF9MWX7Ky6ulp0zz33\neLp06eKpra0Niw8JH7Izf/1E6JCWndXV1VEKhYLRarXMI4884gy0+mebdtYe+UuElC7lFGGXobfT\nmrgoJLIzAIAzZ85IKisrRffffz+n6o3WlSu1rvPcxD2ShHinevbsoMrOampqKDYeWq2Wqa6u5jRw\nHNu1VVt1/QqnOOg6dXUOGjchqLIzAP/9o70UFxdrzWYzpzgYDAZnYmIir3FoircveAAa+4LFYiFy\nEll83aI91+DkFIueCqlzQaeokMjOABqv3l988UUbl2MAAFAXv6OVmEs5xaK1MZMv2VnT4ostFWJs\nK6EaM333aY/sDMB/P2kPoRozffcJRHZmsViopherHk9grlDBZad8yM5omqbmzp0buWbNmqDU3icB\nadmZRqNhampqKACA2tpaKjIyMixU5aRlZ/76RzjAJQ6+ePuCCKCxL0RFRYVFX2DhS3a2Z88eRVVV\nlWj8+PGc7ykJFnzIzprOaITLbA4AP7Izf/1E6JCUnUVGRjJWq/V2Jwh01rdNMxg1TywMW9mZ0+mE\nl19+Wffuu+/WdOzYkfNA2lIWTRLSsrP//u//dhQXF8sHDhzo/O677+QZGRmcBtGWsmiSkJSd1dTU\nUL79gystzTyQhKvsrCkPP/yw4+uvv5Y/99xz9f/+97+lvXr1IuJkaWnmgSR8yM7OnDkjyc3Njfj7\n3/9OAwFam60lBR+ys8jISM+VK1dEIpEINBoN589JKMdMlvbIzvz1Ey6EcsxkCVR2plarmYaGBqq2\ntpb6v//7v98subSG4NZeScvOTpw4Ifvpp5+kf/nLX7QAAG+//XbN4MGDBV8tkLTszGg0NkydOjUq\nJSVFP2TIELvvWptQISk7W79+fYRv/2DXWYVOe+MwevTohsWLF2vZvrBr1y560qRJtilTpug2b94c\n8eKLL9bJ5c1OfAkSPmRnCxcu1JrNZtGzzz6r12g0nl27dhE5qfANH7KzuXPn1mZmZkYDACxfvjxs\nZn1Jy8789ZNQHFegkJadzZgxozY9PV0vl8uZDz/8MKD+gLIzBEEQBEHaRUuyM8Hdg4EgCIIgSPiD\nCQaCIAiCIMTBBANBEARBEOJggoEgCIIgCHEwwUAQBEEQhDiCSTD4kp1du3ZNlJiYaOjSpUtHp1P4\nX4QhEQd/YjOLxUI9//zz0UajUZ+TkyN40RcfsjN/EjihwzUO/sRmly9fFqempupHjhyp37179511\nxAUMn7KzLVu2KP/rv/4rNjMzMyp0R9h2SMXCn9isqKhIzsqtSktLBVfKwBe+ZGf+RHBChkQc/InN\ntm/frkxOTjakp6dHB+qwEkyCAcCP7Cw6Otrz5Zdf0n/4wx/CphIb1zj4E5tt3rxZlZ6eXm8y974R\nGwAAIABJREFUmejjx4/LKioqBPW39wdp2Zk/CVw4wCUO/sRm2dnZ6nnz5tXk5eXRO3bsUIVD4s3C\nl+zMaDTaP/30UyJFtoIFiVj4E5utWrVK/eWXX9IbNmyoWrZsWVicXPmQnfkTwQkdrnHwFZs5nU7Y\nsmVLREFBgXn+/Pm12dnZAZm4BXWS4UN2plQqwV9lSyHDNQ7+xGaXL1+W9O3b1wkA0LNnT9fJkyd/\nd7IzfxK4cIBLHPyJzX799Vdx3759XRKJBAwGg+f8+fOCv0pl4Ut2FhMT42H7SbhAIhbNic3UajXT\nqVMnz+XLl8PC8sWH7MyfCE7ocImDP7EZTdOijh07uiUSCfTr18/JFuVqK236RK3595qIX6y/cOpo\n8Zp454wHZ4RMdkaKk3nXtJZbDZxOzlEdFM6HR3fmTXbmT2yWkJDgOnLkiKxXr16u48ePy3r27Mmp\nPLTz4E0tU2HnFAcqRu6UJsUFXXZGkqvXVmgbGs5zioNCkeDs0vkNXuLgT2wWHx/vOnLkiOzJJ590\nnD59WkZKW7/s4CXtzxU2TrG4L0blnJvUPWSyM1Jkn83WXqjlJvhqbcwkEYvmxGY3b94UWSwW0S+/\n/MI56wrVmOm7T3tlZ6QI1Zjpu09zcfAnNjMYDJ4rV66IrVYrdfToUVmgkkxBzWAA8CM7C0e4xMGf\n2Gzy5Mm2kpISWUZGRnRsbKw7NjY2LJYJSMvOwpX2xsGf2GzWrFnWrVu3qiZNmqSLj493xcbGhkXZ\neBa+ZGfhCNdY+BObvfPOOzWZmZm61atXq/v37x828eFDdhaOtDcO/sRmEokEZs2aVTt27NjooqIi\neY8ePci7SKbfPz1sZWekaSmLJgmXOPgTm6nVambTpk0Wl8sFmZmZukGDBnEaOFrKoklCUnbGBy3N\nPJCkvXHwJzaTy+Wwc+fOKpvNBi+//LKOXU7iSkszDyThQ3ZGmtZma0nBNRb+xGaDBw925ufn0+fO\nnRNv3LiR8w3hoRwzWdojOyNNKMdMlpbi0JzYLDU11Z6ammo/fPiwLNCldcEtOpKWnXXp0sWdkZGh\nLysrkz777LP6+fPn1zzyyCOCv6uNSxymTp1a5ys2O3nypHThwoVaiqLgtddes6pUquAcCEdIys7M\nZrPIVwJH6uTKN+2Nw+zZs62+YrN9+/bJ161bpxaLxfDOO+/UBKpgDjV8yM5MJpM8JydH/euvv0pe\nfPFF3d/+9rewuLmPayz8ic2WL1+uPnLkiFyn03lWr179u5Wd5ebmqnxFcKE4rkDhEgd/YrPZs2dr\nz507J+3cubN71apVKDtDEARBEIR/UHaGIAiCIEhQwQQDQRAEQRDiYIKBIAiCIAhxMMFAEARBEIQ4\nmGAgCIIgCEIcwSQYfMnOAADefPNN7YgRI/Rz5szRBv3AAoQv2dmNGzdERqNRbzQa9VOnThW80IkP\n2Zm/uAgdPmRn//73vyXDhw83DB8+3LBo0aKwcE0A8Cs7u3btmig1NVU/bNgww8GDBwMqhxwK+JSd\nffbZZ4qhQ4cakpKSDHl5eYKX4fElO/MXGyHDl+xs7dq1EUlJSYbk5GTD0aNHA6qDIZgEA4Af2dmp\nU6ekdXV1VEFBAe1wOKjvv/9e8A4OPmRnn376qXL8+PE2k8lEi8Vi5scffxT8B4a07MxfXIJ7RO2D\ntOxs8+bNqvnz59fs37/ffOrUKWlVVVXYCBf4kp2tXr1aPXfu3JrPP/+cXr16dVgkXXzJzjZs2KDO\ny8uj8/Lybn92hA4fsjN/sRE6pGVnAAC7d+9W7d+/35ybm1uZk5ODsrOmsrMTJ05IExMT7QAAiYmJ\n9hMnTgj+6oQP2VlCQoKLLRlttVpFkZGRgpd+kZad+YtLUA6EI6RlZ96+QLH9RS6XC74vsPAlOyst\nLZUOHjzYqdFoGLVazTTdX6jwJTvr1q2bq66ujrJaraJwkQPyITtrTgQnZEjLzgAAOnfu7LLb7VBd\nXS3S6XQBaQXadBVrW50d4b5wgZPsTJIQ71TPnh102VlNTY2IPdlotVpPaWkppyv3Y7u2aquuX+F0\nYtJ16uocNG5CUGVnycnJ9qVLl2q3bt2q6tevn9Pf1W4gFBcXa81mM6c4GAwGZ2JiYtBkZ/7iwqX9\nAACLr1u05xqcnOLQUyF1LugUFTTZ2dNPP20fN26cfuHChZCWllZPqqqruvgdrcRcyikWLkNvpzVx\nUdBlZx6PB9iKphqNxmOxWESRkZHt/oxYV67Uus5zk521NmbyJTsbOXJkw9ChQ2MYhoFAKzf6I1Rj\npu8+gcrOmhPBtZdQjZm++wQiOwMAeOyxxxyDBw+Odbvd1I4dO+hA2iu4rIy07Eyr1XqaiL/C4sod\ngLzsLCcnJ2LmzJm1x44dq9BoNJ5//vOfgp/JASArO/MXl+AcBXdIys6ysrK0GzZsqDpx4kR5aWmp\n5OLFi2Gh5GbhQ3bWVPpltVpFUVFRYdE3+JCdrV69WvPNN9+Uf/vtt+WrVq0Ki3uVAMjLzvzFJhwg\nKTurrq6mvvjiC+WJEyfKCwoKKhYtWhTQfYxtuppXzZwRtrKzgQMHOrds2aLKyMhoKC4ulv/xj3+0\ncWlfS1k0SUjLzo4dOyZnp7d0Ot3tE217aSmLJglJ2Zm/uHBtX0szDyQhKTtjGAZ0Op1HLBaDRqO5\nY1DhQkszDyThQ3bWp08f59GjR6V9+/Z1eZNPThcirc3WkoIP2ZlMJmNUKhVDURQ4nU7OfSOUYyZL\ne2Rn/mLDhVCOmSyBys5EIhEoFApGLpdDZGQkU19fH1B/ENyNfqRlZ/3793fu3LmTGTFihP7+++93\nDhw4MCycKqRlZ5mZmXWvvfZa1KpVqyAqKsozZ86c2uAcCTdIys6MRmODb1yCezTth6TsbPr06dZX\nXnlFJxaLmYSEBFffvn0DUjCHGj5kZ//zP/9jfeWVV3QNDQ1UuHw2APiRnU2YMKFuxIgRBgCAF154\ngdMFWTAhLTvzF5twgKTsTKPRMImJifbk5GSDx+OBWbNmBfTZQNkZgiAIgiDtAmVnCIIgCIIEFUww\nEARBEAQhDiYYCIIgCIIQBxMMBEEQBEGIgwkGgiAIgiDEEUyCQULydfr0acljjz0W89BDD8Wy+1ss\nFur555+PNhqN+pycHMHX1edLdrZ161YlKztLSEiI++GHHwT3FeWmcJV8FRYWyh955JGYptsvX74s\nTk1N1Y8cOVK/e/duwUucAPiRnX3wwQdqti9069YtjqbpsKgiRErwtXz5cvUDDzzQoanoqaioSM5K\nnrhW+w0GfMrOJk2apDMajfrk5GTDk08+GRO6o2wbJCRfM2bMiOzVq1eHzZs33y5ru337dmVycrIh\nPT09Ohy8RXzJztixIjExMWb8+PG6QNokqKBxlXzFx8e79+/fb25apWzz5s2q9PT0epPJRB8/flxW\nUVEhqGP2Bx+yswkTJtSbTCZ6z549dKdOndz9+vUTfO0DLpKvgQMHOoqLiyuabsvOzlbPmzevJi8v\nj96xY4fK6QyPb16Tlp29/vrrVpPJRG/ZsqXqwQcfdOr1+rCobgtARvA1ceJE29q1a+/QC6xatUr9\n5Zdf0hs2bKhatmzZXSm2aqvsbMuWLVUmk4l+9dVXrUOHDvVbDVJocJV8vfHGG7Xz58+/XU/G6XTC\nli1bIgoKCszz58+vzc7ODouKpnzIzkwmE20ymehnn33Wlpyc3GxRP38I6mTLVfKl1WoZXznP5cuX\nJX379nUCAPTs2dN18uRJwQuu+JCdsfsdOXJENnDgQDvrXRAyXCRf0dHRjEJx5yTFr7/+Ku7bt69L\nIpGAwWDwnD9/XvBXqgDkZWfscyaTSc56WsIFEoKvuLg4j7/Sz2q1munUqZPn8uXLYVE6nS/ZGcu+\nffsUzZWbFhpcZWe+RfdomhZ17NjRLZFIoF+/fk62GJXQ4UN2xnLgwAHFqFGjAuoPbRpgT5tuRFTf\nsnP60EV1UDgfHt05KLKzpiQkJLiOHDki69Wrl+v48eOynj17crpydx68qWUq7JySFCpG7pQmxQVV\ndsa+dn5+vjI1NZVzieyr11ZoGxrOc4qDQpHg7NL5DV5lZ02Jj493HTlyRPbkk086Tp8+LbNYLJyX\nBpYdvKT9ucLGKQ73xaicc5O6B012xj5XUFCgzMrKqvb3e+0h+2y29kItN8FXvCbeOePBGUGRnfly\n8+ZNkcViEf3yyy+cE8+Tede0llsNnGLR2pjJl+wMAMDhcEBZWZm0f//+nKf5QjVm+u7TmuysKQaD\nwXPlyhWx1Wqljh49KiMhRgzVmOm7T6CyMwCAW7duiSiKgtjY2ICqHwvuMpar7MyXyZMn20pKSmQZ\nGRnRsbGx7tjYWE4W0WBBWnYG0NhhSkpKZE888YQjVMcVKFxkZ77MmjXLunXrVtWkSZN08fHxrkA/\nLKGEpOwMoDHxqKysFLGa6nCChOzMl3feeacmMzNTt3r1anX//v3D9vPhS3tkZwAAxcXF8pYcN0KE\nq+ysKRKJBGbNmlU7duzY6KKiInmPHj0Ev6TMQlJ2xpKfn68YPnx4wLNZbcrU/8vYMSxkZ9HR0b9Z\nS1ar1cymTZssLpcLMjMzdYMGDeI0eLSURZOEtOwMAKCkpET6wAMPOFn5FxdayqJJ0l7Jlz/i4uI8\nO3furLLZbPDyyy/revTowfnk2tLMA0lIys4AAPbv3y9/+umniU5/tzTzQBKugi9/rzl48GBnfn4+\nfe7cOfHGjRs53wze2mwtKfiQnQEAmEwmRXp6OueZToDQjpksrcnO/JGammpPTU21Hz58WEZiaT2U\nYyZLoLIz9rnCwkLFBx98EPBsp+DWoLlIvp555pn6adOm6X7++WdpWlqaPjs721JZWSlauHChlqIo\neO2116wqlcrfSwgO0rIzgMYsdNSoUUQGjWDRXsnX6NGjGxYvXqxl+8KuXbvor7/+Wr5u3Tq1WCyG\nd955pyYc7kNhISk7A2hcVpk9e3abl5eEBFfBV2FhoeKvf/2rqrq6WmSxWESrV6+uXr58ufrIkSNy\nnU7nWb169V0ptmJpTXbm8Xjg9OnTspUrVxJbPgsGXCRfx48fl7H73bx5UzRv3jzr7NmztefOnZN2\n7tzZvWrVqruyT7QmOwNovGenpqZG1K1bt4AvyFB2hiAIgiBIu0DZGYIgCIIgQQUTDARBEARBiIMJ\nBoIgCIIgxMEEA0EQBEEQ4mCCgSAIgiAIcQSTYPAlO7tx44aIlbVMnTo1KugHFiB8yc4AGiVXaWlp\neqPRqG/6WkKED9nZv//9b8nw4cMNw4cPNyxatCgsfBN8yM7cbje89dZb2rS0NP2ECRMCkheFEj5l\nZ5999pli6NChhqSkJENeXp7gRXh8ys5omqYmTpyoS01N1S9fvlzwDg6+ZGdr166NSEpKMiQnJxuO\nHj0qeMUEX7KzS5cuiZ9//vnoUaNG6XNzcwOq8yCYBAOAH9nZp59+qhw/frzNZDLRYrGY+fHHHwVX\n+8MXPmRnJ06ckNpsNmrv3r20NxahPMQ2QVp2tnnzZtX8+fNr9u/fbz516pS0qqoqLCyipGVnX3zx\nhaJnz56uvXv30lu3bm22zL4Q4Ut2tmHDBnVeXh6dl5dnXr9+veCtywD8yc6WLVumeeutt2q/+uor\n+s033wyLWimkZWcAALt371bt37/fnJubW5mTkyP4RAuAH9nZe++9p1m7dq0lPz+fnjx5si2Q9ggq\nweBDdpaQkOBiSyVbrVZRZGSk4M2RfMjOCgsLFTRNi0aNGqVfunRpWHxYSMvOvH2BYuMkl8sF3xcA\nyMvOioqKFGVlZRKj0aj/5JNPwqPynBe+ZGfdunVz1dXVUVarVeQ7hggVvmRnZWVl0lWrVqlHjRql\nD4crdwDysjMAgM6dO7vsdjtUV1eLdDpdWGgFSMvOHA4HXLt2TTxz5szIZ555JrqsrCygK9M2Xc2f\n2P23CMv1q5wueXWdujoHjZsQdNnZgAEDnEuXLtVu3bpV1a9fP6e/q7xAKC4u1prNZk4fOoPB4ExM\nTAyq7MxsNot0Op0nPz+fnjRpku7UqVOcREaLr1u05xqcnOLQUyF1LugUFTTZ2dNPP20fN26cfuHC\nhZCWllZPoqqruvgdrcRcyikOLkNvpzVxUdBkZxUVFaKBAwc6Fi9eXDNmzBi90WhsiIuL4zyAWleu\n1LrOc5OdSRLinerZs4MuOxs5cmTD0KFDYxiGARJVG4/t2qqtun6FUyxaGzP5kp2dPn1aduDAgQqd\nTueZNGmSrrCwkOZyHKEaM333CUR2BgDw2GOPOQYPHhzrdrupHTt2cIoBQOjGTN99ApGdmc1mUVlZ\nmfTYsWPlFRUVonfffVe7c+fONs96CmoGA4C87CwnJydi5syZtceOHavQaDSef/7zn2Gh3SUtO9No\nNMyjjz7qAAB47LHH7KWlpYJfKgIgKzvLysrSbtiwoerEiRPlpaWlkosXLwp/ncgLSdmZVqtlHn/8\ncbtUKoWHH37YceHChbCJAwA/srPVq1drvvnmm/Jvv/22fNWqVWExwwfAj+yse/furj59+rji4uI8\n4VROn6TsrLq6mvriiy+UJ06cKC8oKKhYtGiRlmxr+YOk7CwyMpJhxZAPPPCAq6mNuS206SQzMOPF\nsJWdMQxDsdNbOp3u9om3vbSURZOEtOzM4/FQ//rXvyTDhw+3nz17Vjp27NiA1tJ8aSmLJglJ2RnD\nMKDT6TxisRg0Gs0dH6b20tLMA0lIys4GDBjgOHv2rLR3797u0tJS6ZQpU+pItLGlmQeS8CE7k8lk\njEqlYiiKAqfTyblftDZbSwo+ZGc9evRwXb9+XaTVahmXy8U5FqEcM1kClZ2JRCJQKBSMXC6HyMhI\npr6+nnMcQjlmsgQqO4uIiGAiIiI8dXV1VFVVFRXo8qHgrmJJy84yMzPrXnvttahVq1ZBVFSUZ86c\nObXBORJukJadjRw5smHatGlRRqNRHx8f73r00UfDwi1DUnY2ffp06yuvvKITi8VMQkKCq2/fvmGj\nYCYpO5s4caJt6tSpURs3blQnJiY2dO3aNSzWl1n4kJ1NmDChbsSIEQYAgBdeeIFT8h1M+JCdzZ07\nt3bKlCk6u91OzZ49OyzGSwDysrPExER7cnKywePxwKxZs34XcfAnO5s5c6b1ueeei3a5XFRWVlZA\nAjyUnSEIgiAI0i5QdoYgCIIgSFDBBANBEARBEOJggoEgCIIgCHEwwUAQBEEQhDiYYCAIgiAIQhzB\nJBh8yc62bt2qZGVnCQkJcT/88IPgvprbFL5kZ6zsyGg06l966aW7TvrWFtnZBx98oGb7Qrdu3eJo\nmha8i4QP2RkrPzIajfr58+eHTQEhPmVnkyZN0hmNRn1ycrLhySefjAnNEbYdPmVnL7/8clRSUpLB\naDTqd+7cqQzdUbYNvmRn7FiRmJgYM378eMFLAfmSnbFxMBqN+kOHDgVUqFIwCQYAP7KzCRMm1JtM\nJnrPnj10p06d3P369RN87QM+ZGcAjZX8TCYTvWHDBs6lkIMBadnZ66+/bjWZTPSWLVuqHnzwQade\nrw8L5wRp2RlAo/zIZDLRS5YsCUrxH1LwJTvbsmVLlclkol999VXr0KFD/VZAFBp8yc4AAD766KMq\nk8lEjx8/vj4UxxYofMjOTCYTbTKZ6GeffdaWnJwcUFG/UMGH7AwAYM+ePbTJZKKHDBniCKQ9gkow\n+JCdsRw5ckQ2cOBAeziUvuVDdgYAkJeXpxwxYoR+165dgr8qASAvO2MxmUzyYcOGhcVJBIC87AwA\nYNOmTREjR47U/+Mf/wiL0vksfMnOWPbt26dorsSy0OBLdkZRFLz66qu6sWPHRl+6dCksysjzITtj\nOXDggGLUqFF3dZ8A8C87A2isajpmzBj9pEmTdIHO+rZpucB9qDzCbXZw6mhUjNwpTYoLuuyMJT8/\nX5mamso5G796bYW2oeE8J2GNQpHg7NL5jaDKzp566qmGo0ePljscDuqZZ57RDxkyxB4bG9vuCo7L\nDl7S/lxh4xSH+2JUzrlJ3YMmO2MpKChQBlqRrjmyz2ZrL9RyE3zFa+KdMx6cETTZWWpqasMLL7xQ\nT9O0KCMjQ5+YmFghkXBfOTyZd01rudXAKRZRHRTOh0d3DrrsDADA4XBAWVkZJwkgi/PgTS1TYecU\ni9bGTL5kZ0uWLKnW6/XMN998I1uwYIF227ZtbZZb+SNUY6bvPoHKzgAAbt26JaIoCriMlSyhGjN9\n9wlEdgYAsGXLlkq9Xs/s3LlT+f7772uWLVvW5llPwV3Ok5adATQGqqSkRPbEE08ENL0TSviQnclk\nMlCr1cwjjzxiP3/+fFhcmZCUnQE0nnArKytF9957LyerbrAhKTvT6XSMWCyG2NhYT48ePVzsmm24\nwIfsDACguLhYHqjfJtTwITtjlw4ff/xxR0VFRdj0DZKyM5b8/HzF8OHDw2L2goWk7AzgP/0hLS2t\nnp0BbStt2lk8JDZsZWcAACUlJdIHHnjASeIqraUsmiSkZWfV1dVUZGQk43K54Mcff5RNnTqVk+Cq\npSyaJCRlZwAA+/fvlz/99NPEBoyWZh5IQlJ2xvYFm80GFy9eFMfExBBxkbQ080ASPmRnAAAmk0mR\nnp5O5J6D1mZrScGH7IztH6WlpWJ2JpQLoRwzWQKVnbEUFhYqPvjgAyKznaEcM1kClZ0B/Kc/fPfd\nd7J77rknoARNcN+oIC0769Gjhzs/P18xatSosLhZiYW07Gzz5s2q7du3q0QiEaSlpdV37tw5LARX\nJGVnSqUS9u3bp5g9e3bAyyqhhqTs7IMPPog4fPiwgmEYeO2116wyWVjdhsGL7Mzj8cDp06dlK1eu\nJHIyCRZ8yM5eeuklXXV1NUVRFLz//vthEw/SsrPq6mqqpqZG1K1bt7Ca7SQtOxszZozea5Zl1q5d\nG9AXBFB2hiAIgiBIu0DZGYIgCIIgQQUTDARBEARBiIMJBoIgCIIgxMEEA0EQBEEQ4mCCgSAIgiAI\ncQSTYPAlOwNolFylpaXpjUajvulrCRG+ZGcsc+bM0WZmZv4uZWdutxveeustbVpamn7ChAmClxcB\n8CM7Yxk3bpzOV3YkZPiUndE0TU2cOFGXmpqqX758udp/C4QDn7IzAACbzQZ9+vTpcPDgQcF/h5kv\n2dmlS5fEzz//fPSoUaP0ubm5KhA4fMnOAACuX78u6tq1a8eff/45oAKNgkkwAPiRnZ04cUJqs9mo\nvXv30iaTiRaLhV/Aki/Z2c2bN0VXrlwRXO2T5iAtO/viiy8UPXv2dO3du5feunUrp/LHwYQP2dmZ\nM2ckdrtd8DZZX/iSnS1btkzz1ltv1X711Vf0m2++GRZ1UviUnW3ZsiWiV69eYVOagA/Z2XvvvadZ\nu3atJT8/n548ebKN/6PgDl+ys3Xr1kX069cv4ErYgkow+JCdFRYWKmiaFo0aNUq/dOlSwV+ZAPAn\nO1u3bl3En/70J04VPIMJadlZUVGRoqysTGI0GvWffPKJ4K9IWPiQna1fvz5i0qRJYTFoNoUv2VlZ\nWZl01apV6lGjRumPHj3KyRcRLPiSndntdjh58qR0wIABYZNgkJadORwOuHbtmnjmzJmRzzzzTHRZ\nWZnwr0yBH9lZRUWFqLa2VtSlS5eAp//bdDV75MiRCJqmOQXYYDA4ExMTgy47M5vNIp1O58nPz6cn\nTZqkO3XqFCeZ0eLrFu25BienAainQupc0CkqqLIzmqYpmqZFCQkJRHT16uJ3tBJzKac4uAy9ndbE\nRUGTnVVUVIgGDhzoWLx4cc2YMWP0RqOxIS4ujlNFU+vKlVrXeW6yM0lCvFM9e3bQZGelpaUSvV7v\niYyMJFrN9diurdqq61c4xULXqatz0LgJQZednT59WnbgwIEKnU7nmTRpkq6wsJDmchzFxcVas9nM\nKRatjZl8yc62bdumysjIqC8pKSGyPBKqMdN3n0BkZ2azWVRWViY9duxYeUVFhejdd9/V7ty5k9Os\nZ6jGTN99ApWdrVu3LuKll16qW7NmTcAX6IKawQAgLzvTaDTMo48+6gAAeOyxx+ylpaVhsURAWna2\nbt06dWZmZtjMXrCQlJ1ptVrm8ccft0ulUnj44YcdFy5cCIurEgCysrMPP/wwgquLJpTwITvr3r27\nq0+fPq64uDgPK3kKB0jLzpxOJxw+fFiekpISVtI3ALKys8jISCY+Pt4VGxvreeCBB1wWiyVsOgVJ\n2VlVVRV1/fp1caBSSZY2nWyfeOKJsJWdDRw40PGvf/1LMnz4cPvZs2elY8eO5TQt3FIWTRLSsrOv\nvvpKuXjxYq3dbqcuXbok2b17tyIjI6Pd0q+WsmiSkJSdDRgwwHH27Flp79693aWlpdIpU6ZwPsm2\nNPNAEpKys6tXr4pfffXVKNbF8dRTT9kTExM5m4ZbmnkgCR+ysx49eriuX78u0mq1jMvl4nxvSmuz\ntaQgLTu7deuW6Pr16+L09PToy5cvSw4dOiTv378/3ZxIsi2EcsxkCVR2FhERwURERHjq6uqoqqoq\nynfpvT2EcsxkCVR2du7cOckvv/wiSU9Pjz537pz05s2b4r1797Z5dk9wV/OkZWcjR45smDZtWpTR\naNTHx8e7Hn300bBYVyQtO9uwYYMFAODixYviJUuWaLgkF8GEpOxs4sSJtqlTp0Zt3LhRnZiY2NC1\na9ewEL4BkJWdffnll5UAjXeRFxcXy0kkF8GED9nZ3Llza6dMmaKz2+3U7Nmza4N8SO2GtOysS5cu\nnkOHDpkBGm9yHDRokJ1LchFMSMvOZs6caX3uueeiXS4XlZWV9buQvvnKzrp16+YuKioyAwC8/PLL\nUa+//npAnw2UnSEIgiAI0i5QdoYgCIIgSFDBBANBEARBEOJggoEgCIIgCHEwwUAQBEEQhDiYYCAI\ngiAIQhzBJBh8yc5YyY/RaNS/9NJLd53kq62yswMHDshTUlL0ycnJhnfffVfwgis+ZGfjt3PyAAAT\n5klEQVSs9MdoNOrnz5+vDdrBcIAP2dm2bduUI0eO1A8ZMsTw8ccfh03JdD5lZy+//HJUUlKSwWg0\n6nfu3Kn03wLhwKfsbM6cOVqj0ahPSkoyfPvtt4Ivm86X7MxoNOrZf4cOHfpdSN/8yc4mTpyoMxqN\n+pSUFH1paSnKznyrlKWnp9ebTCaarQUhdPiQnT311FP2wsJCuqioyFxSUiIrLy8X1N/eH6RlZwCN\n0h+TyUQvWbIkKEVvSEBadjZ27Nj6ffv20QcOHDBv3749ItjHwwW+ZGcAAB999FGVyWSix48fXx/M\nY2ovfMnOlixZUmMymehNmzZVZWdnC/5iBIAf2RkAwJ49e2iTyUQPGTIkLGrF8CE727hxY5XJZKLf\neuut2vXr1wdULlxQJxk+ZGcAAHl5ecoRI0bod+3aJfgrEwB+ZGcyWWMC7nK5ICYmxs36KYQMadkZ\nAMCmTZsiRo4cqf/HP/4h+CsSFtKyM7YvOBwOiI+PJ+KmCRZ8yc4oioJXX31VN3bs2OhLly6FRQl5\nvmRnbP+oq6uj7r///rCof0RadgbQWCp7zJgx+kmTJulomg4L8zAfsjMu/aFNlTyv31gZYbef5/Sh\nUygSnF06vxF02dnDDz/sPHr0aLnD4aCeeeYZ/ZAhQ+yxsbHtPrkuO3hJ+3OFjdO04X0xKufcpO5B\nlZ0BAGzatEn10UcfqRMTE+3+Tr6BkH02W3uhlpvkK14T75zx4Iygyc5SU1MbXnjhhXqapkUZGRn6\nxMTEComEWzHbk3nXtJZbDZziENVB4Xx4dOegyc4AAJYuXareuXNnxOTJk4mpyZ0Hb2qZCjunWFAx\ncqc0KS7osrMlS5ZU6/V65ptvvpEtWLBAu23bNk5iq6vXVmgbGs5zikVrYyZfsjOAxiW3M2fOyNas\nWcMpDgChGzN99wlEdgYAsGXLlkq9Xs/s3LlT+f7772uWLVvGadYzVGOm7z6Bys7sdjukpaXpy8vL\nxbm5uZWBtFdQMxgA/MjOZDIZqNVq5pFHHrGfP88tUQoWpGVnAACZmZm2EydOlN+4cUN0+vRpwZWJ\n9wdJ2ZlOp2PEYjHExsZ6evTo4WLXKsMBkrIzAIB58+ZZv//++1smk0nJrseHC3zIzvR6PQMA8Pjj\njzsqKirCtl/4EqjsjGXHjh1VBQUFFVlZWWFxrxIAWdkZwH/6RFpaWn1ZWVlYjJcAZGVnAAByuRwK\nCwvpjRs3VmVlZQW0ZNamoHXqODtsZWfV1dVUZGQk43K54Mcff5RxtUi2lEWThLTsrKGhARQKBYjF\nYlCpVIxSyW21qKUsmiQkZWdsX7DZbHDx4kVxTEwM52WilmYeSEJSdsb2BZlMBgqFgpHLm83PA6Kl\nmQeS8CE7Y/tGaWmpmJ3940Jrs7WkIC07AwBg+4darWaUSiXnWIRyzGQJVHYG8J8+8d1338nuueee\nNicmzRHKMZMlUNmZx+MBl8sFMpkMNBqNJ9CZb8FlZaRlZ19//bV8+/btKpFIBGlpafWdO3cW/L0H\nALzIzlR79+5VejweGDx4sKN3795hsfZOUna2du3aiMOHDysYhoHXXnvNyq4thgMkZWfvvfee5ujR\nozKn00k9++yzNvbEEi7wITt76aWXdNXV1RRFUfD+++/flWIrlpZkZwAAkydP1tXU1Ig8Hg/Mnz//\nrhS/tUV2NmbMGL03AWfWrl0bFl8QACArO7Pb7fDcc8/pKYoCiqJgxYoVAX02UHaGIAiCIEi7QNkZ\ngiAIgiBBBRMMBEEQBEGIgwkGgiAIgiDEwQQDQRAEQRDiYIKBIAiCIAhxBJNg8CU7Y5kzZ442MzPz\ndys7y8/PlycnJxuSk5MN2dnZgvdP8CE7Yxk3bpzOV/IjVPiQnW3atEnF9oVwEHux8Ck7AwCw2WzQ\np0+fDgcPHhT895f5lJ1Nnz49cvjw4YaUlBQ9u03I8CU7AwC4fv26qGvXrh1//vlnwRdo5Et2Nnbs\n2OgRI0boR48efXtbWxFMggHAn+zs5s2boitXrgj+g8LCh+ysb9++roKCAvP+/fvNRUVFCovFIvjq\njXzIzs6cOSOx2+2CP/amkJadDR061F5UVGQ2mUzm9evXCz7ZbAqfsrMtW7ZE9OrVK2y+js+X7GzG\njBnW/fv3m9esWWNZsWJFWCTifMnO1q1bF9GvX7+wEJ0B8CM7y8rKqi4oKKCnTZtm/fDDD1F25vu6\n69ati/jTn/7EqYJnMOFDdtatWze3RCIBkUgEYrH4dhlYIcOH7Gz9+vURkyZNsvHacMKQlp316NHD\nDdBYbpyriyXY8CU7s9vtcPLkSemAAQPCJsHgS3Z27733ugEApFIpiMWCv3AHAH5kZxUVFaLa2lpR\nly5dOFfxDBZ8yM6a9Acm0P7QptFl6c3qiHN2N6ee1lMhdS7oFBV02RlN0xRN06KEhAQilSvVxe9o\nJeZSTsIal6G305q4KOiyM4DGpYNu3bq5uJZDtq5cqXWd5ybukSTEO9WzZwdNdlZaWirR6/Ue1s1C\ngmO7tmqrrl/hFAddp67OQeMmBFV2BgCwceNG1bBhw/z6CtpDcXGx1mw2c4qFwWBwJiYmBl12tm3b\nNlVGRkZ9SUkJkeWRxdct2nMNTk6xaG3M5FN2BgCwaNEizZQpUzhfmIVqzPTdJ1DZ2bp16yJeeuml\nujVr1gR01d4coRozffcJVHYG0GjhXr16tWblypUBVTQV3GUsadnZunXr1JmZmWEze8HCh+zswoUL\n4rVr16qzsrKCUhOfBCRlZx9++GEEVxdNqCAtOzt+/Lj00KFDilmzZhGzqQYL0rIzp9MJhw8flqek\npATkthECfMnOcnJyInr27Ol6/PHHw2Z5gKTsrKqqirp+/bo4kPFFKJCWnQEAzJs3T5uRkWFLSEgI\naDanTTMY8+Iiw1Z2duXKFfHixYu1drudunTpkmT37t2KjIyMdl+1tZRFk4S07KympoaaNm1aVE5O\njsXfMlKgtJRFk4Sk7Ozq1aviV199NYp1UDz11FP2xMRETgNoSzMPJCEpO7t69apo4cKF2u3bt1eS\nXCJpaeaBJKRlZ7du3RJdv35dnJ6eHn358mXJoUOH5P3796f9jSdtpbXZWlLwITs7cOCAvKSkRJab\nm8tZ1Q4Q2jGTJVDZ2blz5yS//PKLJD09PfrcuXPSmzdvivfu3UtzaV8ox0yWQGVnAI33cVEUBS++\n+GJ9oG0R3AIsadnZhg0bLAAAFy9eFC9ZskTDJbkIJqRlZ++//7766tWrkunTp0cBAOTk5FjYtTUh\nQ1J29uWXX1YCNN49XVxcLOeaXAQTkrKzFStWaMxms3jChAnRAAC7d++mVSoVhAt8yM4OHTpkBgB4\n7733NIMGDbJzSS6CCR+ys7fffjtSrVZ7UlNT9fHx8a41a9aEhfyNtOysqKjIDADw8ssvR73++uu/\nC+mbr+wMoLE/9OvXz2E0GvWDBg1yLFiwoM2xQNkZgiAIgiDtAmVnCIIgCIIEFUwwEARBEAQhDiYY\nCIIgCIIQBxMMBEEQBEGIgwkGgiAIgiDEEUyCwZfs7MCBA/KUlBR9cnKy4d133xV8XX2+ZGctieCE\nCB+ys23btilHjhypHzJkiOHjjz8Oi+9l8iE7a0kEJ2T4lJ3NmTNHazQa9UlJSYZvv/2WU7XFYMCn\n7Kw5GZxQ4Ut2NnHiRJ3RaNSnpKToS0tLBV8znS/ZWXMiuLYgmAQDgB/Z2VNPPWUvLCyki4qKzCUl\nJbLy8nJBHbM/+JCdNSeCEzKkZWdjx46t37dvH33gwAHz9u3bw0byRVp21pwILhzgS3a2ZMmSGpPJ\nRG/atKkqOzs7LE6sfMnOmpPBCRk+ZGcbN26sMplM9FtvvVW7fv16IuXC+YYP2VlzIri2IKiTLR+y\nM5msUS3gcrkgJibGzXoZhAwfsrPmRHBChrTsjO0LDocD4uPjw6YEMGnZWXMiuHCAL9kZ2zfq6uqo\n+++/Pyxq/vAlO/MXH6HDh+zs99QnAJqXnfmLTVtpUyXP9w/9GvGzuZ7TFNF9MSrn3KTuQZedAQBs\n2rRJ9dFHH6kTExPtXAfW7LPZ2gu13IQ18Zp454wHZ4REdkaKk3nXtJZbDZziENVB4Xx4dOegyc4A\nAJYuXareuXNnxOTJk4k4OJwHb2qZCjunOFAxcqc0KS7osjPSXL22QtvQcJ5TLBSKBGeXzm8EXXYG\n0LjMdObMGdmaNWs4X70vO3hJ+3OFjVMsWhsz+ZadkSJUY6bvPoHKzux2O6SlpenLy8vFubm5lVza\nDxC6MdN3n/bIztqLoGYwAMjLzgAAMjMzbSdOnCi/ceOG6PTp04Irj+4PPmRn4QhJ2RkAwLx586zf\nf//9LZPJpGTXocMB0rKzcIa07Ixlx44dVQUFBRVZWVlaPtrNB3zJzsIRkrIzAAC5XA6FhYX0xo0b\nq7KyssJi2QyAH9lZe2nTyXbOkHvCVnbW0NAACoUCxGIxqFQqRqlUcmpfS1k0SUjLzki3r6UsmiQk\nZWdsX5DJZKBQKBi5vMW8tE20NPNAEpKyM77a2NLMA0lIy84A/tM31Go1o1QqOV/KtzZbSwo+ZGek\nCeWYyRKo7Mzj8YDL5QKZTAYajcZDYkkxlGMmS3tkZ1wQ3NU8adlZUVGRfO/evUqPxwODBw929O7d\nOyzW3knLzn799VeRb2x69Ogh+Bs+ScrOVq5cqTl69KjM6XRSzz77rI2vAZUPSMrOSkpKpL6x4Zp4\nBxM+ZGeTJ0/W1dTUiDweD8yfP/+uFFuxtCY7y83NVfnGJ4iH1G5Iys5mzpxpfe655/QURQFFUbBi\nxYqwiAEAednZ8uXL1b4iuLa2BWVnCIIgCIK0C5SdIQiCIAgSVDDBQBAEQRCEOJhgIAiCIAhCHEww\nEARBEAQhDiYYCIIgCIIQRzAJBl+ys/z8fHlycrIhOTnZkJ2dLXj/BFe51aZNm1Ts8e7cufOO7x7O\nmTNHm5mZGRWUA+EIH7KzlmIjVEhJraZPnx45fPhwQ0pKip6VWgE0ft//ySefjGmPyCjY8Ck7ay4+\nQoWE2Grs2LHRI0aM0I8ePfq22AoAwGazQZ8+fTocPHhQFtyjah98yc6aiw/SdgQVND5kZ3379nUV\nFBSY9+/fby4qKlJYLBbBl6vjIrcaOnSovaioyGwymczr16+/nVDdvHlTdOXKFcEPnE0hLTtrLjZC\nh4TUasaMGdb9+/eb16xZY1mxYsXtwdVkMsmjo6MFXw+FhS/ZWXPxETJcxVZZWVnVBQUF9LRp06wf\nfvjhbZnXli1bInr16hVWZQn4kJ01Fx+k7QgqweBDdtatWze3RCIBkUgEYrGYSPlTvuEit2KLZ0kk\nEpBI/pNPrFu3LuJPf/pTXRCaTwzSsrPmYiN0SEit7r33XjcAgFQqBbH4PxWzP//8c1VaWprfksJC\nhC/ZWXPxETJcBV9Njplhj9lut8PJkyelAwYMCKsEgw/Zmb/4IIHRplFWe+QvEVK6lFOEXYbeTmvi\nopDIzgAap8y7devmYiVg7cW6cqXWdZ6buEeSEO9Uz57Nq+Rr48aNqmHDhjUAANA0TdE0LUpISCBW\nxfTYrq3aqutXOMVB16mrc9C4CUGVnQHcGRuuFBcXa81mM6c4GAwGZ2JiYlAEX4sWLdJMmTKlDqAx\nQRs8eLBdLBYzLpeL88ze4usW7bkGJ6dY9FRInQs6RYVEdgZwZ3y4oC5+Rysxl3KKRWtjJgnBl8vl\ngtWrV2tWrlxpAQDYtm2bKiMjo76kpITY8kioxkzffQKVnQH8Nj5IYAjucp4P2dmFCxfEa9euVWdl\nZQWlFjwJuEi+jh8/Lj106JBi1qxZVgCAdevWqTMzM8Nq9oKFtOzMNzbhAgnBV05OTkTPnj1djz/+\nuAMAYPv27aoJEybYgnME5OBLduYbn3CAq+Br3rx52oyMDFtCQoLb6XTC4cOH5SkpKQE5foQCadkZ\nwJ3xIdPK3xdtmsGoeWJh2MrOampqqGnTpkXl5ORYfJdP2kNLWTRJ2iu3unr1qmjhwoXa7du3V7LL\nAFeuXBEvXrxYa7fbqUuXLkl2796tyMjI4HQF39LMA0lIys78xYYrLc08kISr1OrAgQPykpISWW5u\n7u3ZvosXL0peeOGF6Fu3bokZhoFHH32Uk6unpZkHkvAhO/MXHy60NltLCi6Cr9zcXBVFUfDiiy/W\nAwDcunVLdP36dXF6enr05cuXJYcOHZL379+f9jeuBkIox0yWQGVnAL+NDxI4gluIJi07++yzz5RX\nr16VTJ8+PQoAICcnx8KurQmZ9sqtLBaLyGw2iydMmBANALB79256w4YNFgCAixcvipcsWaL5/+3d\nMU7CUBzH8Z/BQQlIDImjS3ccGOwVDKGncPMGpGxMjByBwTD3AAxcwMUr1KEaElsXyUufEwtgQdo0\nIN/P+rq8N/3SvP/75Q0XZSqy7Gw4HNZXz6ZaPfjhCUn5S61832/UarW02+02Hccxo9HoczabvUvS\neDy+NMacHXMRYN6ys03nU/K29pKn2Mr3/Uar1Vp0Op2m67qLfr+fTKfTD0kaDAZ113W/84aLMhVZ\ndtbr9b42nU/5uzpulJ0BAIC9UHYGAABKRcAAAACF2xYw0jRdGw8GAAAnzlorm3HPYlvAeJ3P51dZ\n9zQAAMBpsdYqSZKLOI6j377JnCIxxjyGYfhsjLmvVCq5HkoBAAD/g7XWxnEcTSaTQNKNpLVx3syA\n0W63I8/zHiQ9SbqTdPDjnQAAoDTXkiJJL6sLmWOqS57nnUu6lcRfDAAAsJRKeguCYO216J0CBgAA\nwF8wpgoAAApHwAAAAIUjYAAAgML9AJaGEjo6teTlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f564b5b9ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from runAndPlot import run_c302\n",
    "\n",
    "%matplotlib inline\n",
    "cells, cells_to_stimulate, params, muscles = run_c302('AVB_VB','C2','',4000,0.05,'jNeuroML_NEURON',verbose=False, plot_ca=False, data_reader=\"UpdatedSpreadsheetDataReader\", config_package=\"notebooks.configs.AVB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
